Query Reformulation

Nowadays organizations not only are increasing the data volume, but also they have to work with a large variety of data sources with different types of data. The central problem of information sources integration resides on their heterogeneity on the level of their format, the design and/or the semantic aspect. It would be necessary to use some kind of systems like wrappers or mediators in order to get a common format for the information. In this paper we propose a new system to solve this problem, which uses XML as common format. It describes the system architecture and focuses on the distributed query processing technology in this component. Proposed System allows querying, retrieving data from different sources integrate them and translates the results to XML. The goal of such a system is to intercept the user queries and to find the more adequate data from several heterogeneous resources, to answer the queries of the user, and to turn over the result in a transparent way to the ...

Nous présentons dans cet article un logiciel permettant d’assister l’usager, de manière personnalisée lors de la recherche documentaire sur le Web. L’architecture du logiciel est basée sur l’intégration d’outils numériques de traitements des langues naturelles (TLN). Le système utilise une stratégie de traitement semi-automatique où la contribution de l’utilisateur assure la concordance entre ses attentes et les résultats obtenus.

We present an approach to increasing the effectiveness of rankedoutput retrieval systems that relies on graphical display and user manipulation of "views" of retrieval results, where a view is the subset of retrieved documents that contain a specified subset of query terms. This approach has been implemented in a system named VIEWER (VIEwing WEb Results), acting as an interface to available search engines. An experimental evaluation of the performance of VIEWER in contrast to AltaVista is the major focus of the paper. We first report the results of an experiment on single, short query searches where VIEWER, used as an interactive ranking system, markedly outperformed AltaVista. We then concentrate on a more realistic searching scenario, involving free query formulation, unconstrained selection of retrieval results, and possibility of query reformulation. We report the results of an experiment where the use of VIEWER, compared to AltaVista, seemed to shift the user effort from inspection to evaluation of results, increasing retrieval effectiveness and user satisfaction. In particular, we found that the VIEWER users retrieved half as many nonrelevant documents as the AltaVista users while retrieving a comparable number of relevant documents.

In this paper we consider the implications for belief revision of weakening the logic under which belief sets are taken to be closed. A widely held view is that the usual belief revision functions are highly classical, especially in being driven by consistency. W e show that, on the contrary, the standard representation theorems still hold for paraconsistent belief revision. Then we give conditions under which consistency is preserved by revisions, and we show that this modelling allows for the gradual revision of inconsistency.

SPARQL query rewriting is a fundamental mechanism for uniformly querying heterogeneous ontologies in the Linked Data Web. However, the complexity of ontology alignments, particularly rich correspondences (c : c), makes this process challenging. Existing approaches primarily focus on simple (s : s) and partially complex (s : c) alignments, thereby overlooking the challenges posed by more expressive alignments. Moreover, the intricate syntax of SPARQL presents a barrier for non-expert users seeking to fully exploit the knowledge encapsulated in ontologies. This article proposes an innovative approach for the automatic rewriting of SPARQL queries from a source ontology to a target ontology, based on a user's need expressed in natural language. It leverages the principles of equivalence transitivity as well as the advanced capabilities of large language models such as GPT-4. By integrating these elements, this approach stands out for its ability to efficiently handle complex alignments, particularly (c : c) correspondences , by fully exploiting their expressiveness. Additionally, it facilitates access to aligned ontologies for users unfamiliar with SPARQL, providing a flexible solution for querying heterogeneous data.

SPARQL query rewriting is a fundamental mechanism for uniformly querying heterogeneous ontologies in the Linked Data Web. However, the complexity of ontology alignments, particularly rich correspondences (c : c), makes this process challenging. Existing approaches primarily focus on simple (s : s) and partially complex (s : c) alignments, thereby overlooking the challenges posed by more expressive alignments. Moreover, the intricate syntax of SPARQL presents a barrier for non-expert users seeking to fully exploit the knowledge encapsulated in ontologies. This article proposes an innovative approach for the automatic rewriting of SPARQL queries from a source ontology to a target ontology, based on a user's need expressed in natural language. It leverages the principles of equivalence transitivity as well as the advanced capabilities of large language models such as GPT-4. By integrating these elements, this approach stands out for its ability to efficiently handle complex alignments, particularly (c : c) correspondences , by fully exploiting their expressiveness. Additionally, it facilitates access to aligned ontologies for users unfamiliar with SPARQL, providing a flexible solution for querying heterogeneous data.

GridVine is a Peer Data Management System based on a decentralized access structure. Built following the principle of data independence, it separates a logical layer--where data, schemas and mappings are managed--from a physical layer consisting of a structured Peer-to-Peer network supporting efficient routing of messages and index load-balancing. Our system is totally decentralized, yet it fosters semantic interoperability through pairwise schema mappings and query reformulation. In this demonstration, we present a ...

As a simple XML query language but with enough expressive power, XPath has become very popular. To expedite evaluation of XPath queries, we consider the problem of rewriting XPath queries using materialized XPath views. This problem is very important and arises not only from query optimization in server side but also from semantic caching in client side. We consider the problem of deciding whether there exists a rewriting of a query using XPath views and the problem of finding minimal rewritings. We first consider those two problems for a very practical XPath fragment containing the descendent, child, wildcard and branch features. We show that the rewriting existence problem is coNP-hard and the problem of finding minimal rewritings is Σ p 3 . We also consider those two rewriting problems for three subclasses of this XPath fragment, each of which contains child feature and two of descendent, wildcard and branch features, and show that both rewriting problems can be polynomially solved. Finally, we give an algorithm for finding minimal rewritings, which is sound for the XPath fragment, but is also complete and runs in polynomial time for its three subclasses.

We consider the problem of finding equivalent minimalsize reformulations of SQL queries in presence of embedded dependencies . Our focus is on select-project-join (SPJ) queries with equality comparisons, also known as safe conjunctive (CQ) queries, possibly with grouping and aggregation. For SPJ queries, the semantics of the SQL standard treat query answers as multisets (a.k.a. bags), whereas the stored relations may be treated either as sets, which is called bag-set semantics for query evaluation, or as bags, which is called bag semantics. (Under set semantics, both query answers and stored relations are treated as sets.) In the context of the above Query-Reformulation Problem, we develop a comprehensive framework for equivalence of CQ queries under bag and bag-set semantics in presence of embedded dependencies, and make a number of conceptual and technical contributions. Specifically, we develop equivalence tests for CQ queries in presence of arbitrary sets of embedded dependencies under bag and bag-set semantics, under the condition that chase [10] under set semantics (set-chase) on the inputs terminates. We also present equivalence tests for aggregate CQ queries in presence of embedded dependencies. We use our equivalence tests to develop sound and complete (whenever set-chase on the inputs terminates) algorithms for solving instances of the Query-Reformulation Problem with CQ queries under each of bag and bag-set semantics, as well as for instances of the problem with aggregate queries. Some of our results are of independent interest. In particular, it is known that constraints that force some relations to be sets on all instances of a given database schema arise naturally in the context of sound (i.e., correct) chase [9] under bag semantics. We develop a formal framework for defining such constraints as embedded dependencies, provided that row (tuple) IDs, commonly used in commercial database-management systems, are defined for the respective relations. We also extend the condition of [4] for bag equivalence of CQ queries, to those cases where some relations are set valued in all instances of the given schema. Our proof of this nontrivial result includes reasoning involving bag (non)containment. In particular, we provide an original proof (adapted to our context) of the result of [4] that CQ query Q 1 is bag contained in CQ query Q 2 only if, for each predicate used in Q 1 , Q 2 has at least as many subgoals with this predicate as Q 1 does. Our contributions are clearly applicable beyond the Query-Reformulation Problem considered in this paper. Specifically, the results of this paper can be used in developing algorithms for rewriting CQ queries and queries in more expressive languages (e.g., including grouping and aggregation, or arithmetic comparisons) using views in presence of embedded dependencies, under bag or bag-set semantics for query evaluation. This text contains corrections to Sections 2.4 and 4 of [5].

The Hagsgate town episode which was omitted in the animated film.  There are very interesting parts concerning the prophesy and curse set on the prosperous town.  The existence of prince Lír aggregates “antifantasy” elements, through metafiction subject and ludicrous description.

Interoperability plays an important role for a variety of applications. One of them are Peer Data Management Systems, where autonomous data sources (peers) interact with each other based on semantic mappings between their schemas. The building blocks that enable interoperability and thus the main challenges in such systems are mapping representation, query rewriting, and efficient query processing. While most approaches regard these aspects in separate this paper presents a comprehensive study of the interactions between these blocks. Our considerations try to provide a holistic view on semantic interoperability in distributed environments such as PDMS. We discuss techniques for distributed query processing and rewriting that consider high-level query operators such as top-N and skyline. Furthermore, we discuss how to increase efficiency by applying routing indexes and relaxation of result completeness/correctness.

Users of online retrieval systems experience many difficulties, particularly with search tactics, User studies have indicated that searchers use vocabulary incorrectly and do not take full advantage of iteration to improve their queries. To address these problems, an expert system for online search assistance was developed. This prototype augments the searching capabilities of novice users by providing automatic query reformulation to improve the search results, and automatic ranking of the retrieved passages to speed the identification of relevant information. Users' search performance using the expert system was compared with their search performance on their own, and their search performance using an online thesaurus. The following conclusions were reached: (1) the expert system significantly reduced the number of queries necessary to find relevant passages compared with the user searching alone or with the thesaurus. (2) The expert system produced marginally significant improvements in precision compared with the user searching on their own. There was no significant difference in the recall achieved by the three system configurations. (3) Overall, the expert system ranked relevant passages above irrelevant passages.

In order to search across factual knowledge and content explicated using different data formats this paper leverages a generic data model (schema) that transforms keyword-based retrieval models and queries to knowledge-oriented models and semanticallyexpressive queries. As each of the transformed retrieval models capitalises on a specific evidence space (term, classification, relationship and attribute), we demonstrate two possible combinations of these spaces, namely macro-based or micro-based. For bare keyword-based queries we demonstrate how the data model can be used to augment the queries with classifications, relationships, etc. that reflect the underlying constraints and objects found in the heterogeneous knowledge bases. Using the IMDb benchmark the results demonstrate the feasibility and effectiveness of the instantiated retrieval models and the query reformulation process.

Le Web des donnees offre un environnement de partage et de diffusion des donnees, selon un cadre particulier qui permet une exploitation des donnees tant par l’humain que par la machine. Pour cela, le framework RDF propose de formater les donnees en phrases elementaires de la forme (sujet, relation, objet) , appelees triplets. Les bases du Web des donnees, dites bases RDF, sont des ensembles de triplets. Dans une base RDF, l’ontologie – donnees structurelles – organise la description des donnees factuelles. Le nombre et la taille des bases du Web des donnees n’a pas cesse de croitre depuis sa creation en 2001. Cette croissance s’est meme acceleree depuis l’apparition du mouvement du Linked Data en 2008 qui encourage le partage et l’interconnexion de bases publiquement accessibles sur Internet. Ces bases couvrent des domaines varies tels que les donnees encyclopediques (e.g. Wikipedia), gouvernementales ou bibliographiques. L’utilisation et la mise a jour des donnees dans ces bases s...

With the exponential growth in web users, search history is also growing exponentially. To manage the web search , search engine uses different techniques. It gives users an easy feel to search their interest by providing page ranking, web personalization and other tools. Most of the search engines store search history in search query and respective click format. We are using query grouping mechanism to store user’s history so that she will get her previous related searched data easily.

Executive Summary Digital libraries can be viewed as an infrastructure for supporting both the creation of information sources and the movement of information across global networks, and moreover the effective and efficient interaction among knowledge producers, librarians, and information and knowledge seekers. Typically, a digital library is a vast collection of objects, which are stored and maintained by multiple information sources, including databases, image banks, file systems, e-mail systems, the WWW, and others. These ...

Data warehouses are nowadays an important component in every competitive system, it's one of the main components on which business intelligence is based. We can even say that many companies are climbing to the next level and use a set of Data warehouses to provide the complete information or it's generally due to fusion of two or many companies. these Data warehouses can be heterogeneous and geographically separated , this structure is what we call federation, and even if the components are physically separated, they are logically seen as a single component. generally, these items are heterogeneous which make it difficult to create the logical federation schema ,and the execution of user queries a complicated mission. In this paper, we will fill this gap by proposing an extension of an existent algorithm in order to treat different schema types (star , snow flack) including the treatment of hierarchies dimension using ontology

We support exible query processing with autonomous networked information sources. Flexibility allows a query to be accepted in a dynamic environment with unavailable sources. Flexibility provides the ability to identify equivalent sources, based on their contents; these equivalences are used to eliminate redundancy and provide alternate query plans, when some source is unavailable. We determine the best plan, i.e., the least-cost non-redundant plan, based on a cost-model for autonomous sources. These features are supported by a meta-wrapper component within the mediator. The meta-wrapper interface is de ned by a structure and supported operations. WHOQL is a query language for queries and plans; it can represent sequential execution to obtain safe plans, and plans with redundancy (alternatives). A language WHODL de nes the mapping from the meta-wrapper interface to each source. WHODL also describes the contents of a source. This content de nition is used to determine equivalences of autonomous sources. We obtain a least-cost non-redundant plan in a dynamic environment. A metawrapper cost model uses three underlying sources of information: a selectivity model; a cost model for operators in the meta-wrapper; and a cost estimator for the query response time. The estimator uses a parameterized feedback technique to learn from query feedback, and to determine the relevance of various factors that a ect response time. The cost model also provides feedback to the plan generator on low-cost plans.

We propose an intelligent and an efficient query processing approach for semantic mediation of information systems. We propose also a generic multi agent architecture that supports our approach. Our approach focuses on the exploitation of intelligent agents for query reformulation and the use of a new technology for the semantic representation. The algorithm is self-adapted to the changes of the environment, offers a wide aptitude and solves the various data conflicts in a dynamic way; it also reformulates the query using the schema mediation method for the discovered systems and the context mediation for the other systems.

With evolving Web, short length parallel corpora is becoming very common and some of these include user queries, web snippets etc. This paper concerns situations where short length parallel corpora has to be analyzed in order to find meaningful unit-alignment. This is similar to dealing with parallel corpora where a sentence level alignment of translations is required, but differs in that the alignment is to be inferred at unit (word or phrase) level. A Conditional Random Field (CRF) based approach is proposed to discover this unit alignment. Given pairs of semantically or syntactically similar entities, the problem is formulated as that of mutual segmentation and sequence alignment problem. The mutual segmentation refers to the process of segmenting the first entity based on units (or labels) in the second entity and vice-versa. The process of optimizing this mutual segmentation also results in optimal unit alignment. Since our training data is not segmented and unit-aligned, we modify the CRF objective function to accommodate unsupervised data and iterative learning. We have applied this framework to Web Search domain and specifically for query reformulation task. Finally, our experiments suggest that the proposed approach indeed results in meaningful alternatives of the original query.

With evolving Web, short length parallel corpora is becoming very common and some of these include user queries, web snippets etc. This paper concerns situations where short length parallel corpora has to be analyzed in order to find meaningful unit-alignment. This is similar to dealing with parallel corpora where a sentence level alignment of translations is required, but differs in that the alignment is to be inferred at unit (word or phrase) level. A Conditional Random Field (CRF) based approach is proposed to discover this unit alignment. Given pairs of semantically or syntactically similar entities, the problem is formulated as that of mutual segmentation and sequence alignment problem. The mutual segmentation refers to the process of segmenting the first entity based on units (or labels) in the second entity and vice-versa. The process of optimizing this mutual segmentation also results in optimal unit alignment. Since our training data is not segmented and unit-aligned, we modify the CRF objective function to accommodate unsupervised data and iterative learning. We have applied this framework to Web Search domain and specifically for query reformulation task. Finally, our experiments suggest that the proposed approach indeed results in meaningful alternatives of the original query.

In a number of domains, particularly in bioinformatics, there is a need for complex data analysis. For that issue, elementary data analysis operations called tasks are composed as workflows. The composition of tasks is however difficult due to the distributed and heterogeneous resources of bioinformatics. This doctorial work will address the composition of tasks using Logical Information Systems (LIS). LIS let users build complex queries and updates over semantic web data through guided navigation, suggesting relevant pieces and updates at each step. The objective is to use semantics to describe bioinformatic tasks and to adapt the guided approach of Sewelis, a LIS semantic web tool, to the composition of tasks. We aim at providing a tool that supports guided composition of semantic web services in bioinformatics, and that will support biologists in designing workflows for complex data analysis. This work started in October 2012 under an ARED funding from Region Bretagne and is supervised by Mireille Ducassé (IRISA/INSA Rennes) and Sébastien Ferré (IRISA/University Rennes 1).

The FORUM project aims at extending existing data integration techniques in order to facilitate the development of mediation systems in large and dynamic environments. It is well known from the literature that a crucial point that hampers the development and wide adoption of mediation systems lies in the high entry and maintenance costs of such systems. To overcome these barriers,

,johannes.heinecke}@orange-ftgroup.com RÉSUMÉ. Cet article décrit l'utilisation d'une plateforme de traitement automatique des langues naturelles pour le développement d'une fonction de réponses à des questions dans un moteur de recherche. Cette plateforme est utilisée pour faire une interprétation linguistique des requêtes. L'intérêt de cette approche est triple. Premièrement elle permet d'identifier uniquement les requêtes qui correspondent à des questions factuelles pour lesquelles le moteur a une réponse précise. Deuxièmement, elle reconnait ces questions quelque soit leur forme linguistique y compris avec des erreurs. Troisièmement, elle désambiguïse certains mots de la requête. Une évaluation a pu montré que l'interprétation linguistique de la requête a permis la production d'une réponse à environ quatre fois plus de requêtes avec un taux de précision supérieur à 98% par rapport à une approche plus classique d'indexation de requêtes. ABSTRACT. In this article we describe the use of Natural Language Processing platform to interpred user queries to be fed into a question-answering system. The advantage of this system is threefold: first, we are able to identify only those requests which correspond to factual questions for which the engine has a precise answer; second, error correction is semantically controlled, in order to avoid bad or missing answers due to typos and third the language processing is used to disambiguate ambiguous word forms. With this interpretation we are able to identify and respond to four times as many queries as without interpretation with an accuracy rate > 98%. MOTS-CLÉS : moteur de recherche, moteur de questions réponses, traitement automatique des langues naturelles, web sémantique

The fuzzy information retrieval model was proposed some years ago to solve several limitations of the Boolean model without a need of a complete redesign of the information retrieval system. However, the complexity of the fuzzy query language makes it difficult to formulate user queries. Among other proposed approaches to solve this problem, we find the Inductive Query by Example (IQBE) framework, where queries are automatically derived from sets of documents provided by the user. In this work we test the applicability of a multiobjective evolutionary IQBE technique for fuzzy queries in a machine learning environment. To do so, the Cranfield documentary collection is divided into two different document sets, labeled training and test, and the algorithm is run on the former to obtain several queries that are then validated on the latter.

Automatic query expansion (AQE) is an effective measure to improve information retrieval performance by including additional terms in a user query. The pseudo relevance feedback (PRF) method employed for AQE so far has suffered from a major problem of query drift. Therefore, keeping it in view, a new hybrid document clustering for PRF based AQE approach is proposed in the present article. In this, Fuzzy logic and Particle Swarm Optimization (PSO) are used to construct document clusters. Further, a new and effective hybrid PSO and Fuzzy logic-based term weighting approach is followed to find more suitable additional query terms using a weighted score of four IR evidences which is considered maximized. Moreover, a combined semantic filtering method along with query terms re-weighting algorithms are also used to remove noisy or irrelevant terms semantically. The performance of the presented approaches in this article is tested and compared with other approaches on three benchmark data ...

When computational researchers from several domains cooperate, one recurrent problem is finding tools, methods and approaches that can be used across disciplines, to enhance collaboration through reuse. The paper presents our ongoing work to meet the challenges posed by provenance-based retrieval, proposed as a solution for transdisciplinary scientific collaboration via reuse of scientific workflows. Our work is based upon a case study in molecular dynamics experiments, as part of a larger multi-scale experimental scenario.

Defining a measure of similarity between queries is an interesting and difficult problem. A reliable query-similarity measure can be used in a variety of applications such as query recommendation, query expansion, and advertising. In this paper, we exploit the information present in query logs in order to develop a measure of semantic similarity between queries. Our approach relies on the concept of the query-flow graph, a graph-based representation of a query log. The query-flow graph aggregates query reformulations from many users: nodes in the graph represent queries, and two queries are connected if they are likely to appear as part of the same search goal. Our query-similarity measure is obtained by projecting the graph (or appropriate subgraphs extracted from it) on a low-dimensional Euclidean space. Our experiments show that the measure we obtain captures a notion of semantic similarity between queries and it is useful for diversifying query recommendations.

We introduce a new multimodal retrieval technique which combines query reformulation and visual image reranking in order to deal with results sparsity and imprecision, respectively. Textual queries are reformulated using Wikipedia knowledge and results are then reordered using a k-NN based reranking method. We compare textual and multimodal retrieval and show that introducing visual reranking results in a significant improvement of performance.

Personal agents have been developed that assist a user with information processing needs by generating, filtering, collecting, or transforming information. On the other hand internet stores are providing services customized by the needs and interests of individual customers. Such services can be viewed as "seller's agents" whose goal is to push merchandise and/or services on to the users. This leads us to believe that there is a growing need for deploying "buyer's agents" whose goal is to best serve the consumer's interests. The Internet contains a huge volume of information which can overwhelm a buyer. The buyers may often make misinformed decisions based on partial, outdated, irrelevant or incorrect information. We have identified several key functionalities of buyer's agents whose goal is to reduce information overload and improve relevancy and accuracy of information for consumers. In particular, such agents can make consumers aware of complex interactions between specified preferences and prevailing market conditions, provide differential analysis for decision support, and use domain ontologies to help the user reformulate queries to improve satisfaction with query results. We present SAATHI, a prototype buyer's agent that demonstrate some of these functionalities in an apartment locator domain.

We describe a visualization tool for XPath expressions called XViz. Starting from a workload of XQueries, the tool extracts the set of all XPath expressions, and displays them together with some relationships. XViz is intended to be used by an XML database administrator in order to assist her in performing routine tasks such as database tuning, performance debugging, comparison between versions, etc. Two kinds of semantic relationships are computed and displayed by XViz, ancestor/descendant and containment. We describe an efficient, optimized algorithm to compute them.

Web searching is becoming more and more complex due to increased size of information on the web. Users have to face a lot of problems in specifying their needs in the form of query. Query Reformulation techniques are required in order to provide users with the results, according to their expectations. The existing reformulation techniques suffer from the problem of not providing users with expected results in all the cases because the mechanisms used behind those techniques are not much fine and accurate. A technique for query reformulation has been presented in this paper which is based on Cross-document Structure Theory (CST) and Rhetorical Structure Theory (RST). A case study has been carried out to validate the proposed technique. The results are satisfactory as set of reformulated queries generated through this technique is semantically more close to the original query which ultimately provides more relevant data to the user.

This report describes the activities of SLP Spoken Document Processing Working Group (SDPWG). The SDPWG was organized in 2006. The working group was reorganized in 2009. This report mainly describes the activities of the second period of the SDPWG. The SDPWG organized Interspeech2010 special session, NTCIR-9 workshop, and the special issue on spoken document processing of IPSJ journal. This report focuses the planning process of these activities. 1. はじめに

This is a demonstration of data coordination in a peer data management system through the employment of distributed triggers. The latter express in a declarative manner individual security and consistency requirements of peers, that cannot be ensured by default in the P2P environment. Peers achieve to handle in a transparent way data changes that come from local and remote actions and events. The distributed triggers are implemented as an extension of the active functionality of a centralized commercial DBMS. The language and execution semantics of distributed triggers are integrated in the kernel of the DBMS such that the latter handles transparently and simultaneously both centralized and distributed triggers. Moreover, the management of distributed triggers is associated with a set of peer acquaintance and termination protocols which are incorporated in the centralized DBMS.

Knowledge workers such as healthcare information professionals, legal researchers, and librarians need to create and execute search strategies that are comprehensive, transparent, and reproducible. The traditional solution is to use proprietary query building tools provided by literature database vendors. In the majority of cases, these query builders are designed using a form-based paradigm that requires the user to enter keywords and ontology terms on a line-by-line basis and then combine them using Boolean operators. However, recent years have witnessed significant changes in human-computer interaction technologies and users can now engage with online information systems using a variety of novel data visualisation techniques. In this paper, we evaluate a new approach to query building in which users express concepts as objects on a visual canvas and compare this with traditional form-based query building in a lab-based user study. The results demonstrate the potential of visual interfaces to mitigate some of the shortcomings associated with formbased interfaces and encourage more exploratory search behaviour. They also demonstrate the value of having a temporary 'scratch' space in query formulation. In addition, the findings highlight an ongoing need for transparency and reproducibility in professional search and raise further questions around how these properties may best be supported.

Information searching in web environment is habitually tedious and challenging task. Rapid growth of web information infrastructure has led to the rapid publication of information on web environment. Too many information publish on web cause information overload problem that preclude the success of information searching. Thus, reduce the search satisfaction. This study has identified that user knowledge lead to user search behaviour and user search behaviour lead to search satisfaction. This paper discusses the investigation empirically through the search log analysis and questionnaire. The respondents were among the students at a local university in Malaysia. The findings support that the user search behaviour has a mediator effect on the relationship between the user knowledge and search satisfaction.

N-ary conjunctive queries, ie, queries with any number of answer variables, are the formal core of many Web query languages including XSLT, XQuery, SPARQL, and Xcerpt. Despite a considerable body of research on the optimization of such queries over tree-shaped XML data, little attention has been paid so far to efficient access to graph-shaped XML, RDF, or Topic Maps. We propose the first evaluation technique for n-ary conjunctive queries that applies to both tree-and graph-shaped data and retains the same complexity ...

While a major share of prior work have considered search sessions as the focal unit of analysis for seeking behavioral insights, search tasks are emerging as a competing perspective in this space. In the current work, we quantify user search task behavior for both single-as well as multi-task search sessions and relate it to tasks and topics. Specifically, we analyze user-disposition, topic and user-interest level heterogeneities that are prevalent in search task behavior. Our results show that while search multi-tasking is a common phenomenon among the search engine users, the extent and choice of multi-tasking topics vary significantly across users. We find that not only do users have varying propensities to multi-task, they also search for distinct topics across single-task and multi-task sessions. To our knowledge, this is among the first studies to fully characterize online search tasks with a focus on user-and topic-level differences that are observable from search sessions.

The paper deals with assisting e n d-users in accessing a European Reliability Data System-the design of an inte l ligent int.erface aimed at large and complex technical data base (namely, the ERDS) in a friendly , correct , and effective way. The interface incl u des both natural language understanding and expert problem solving capabil i ties and features a modular archit e cture devoted to cope with the exigencies of both technical and non-technical users. In the paper a brief introduction to ERDS is first presented and the problems related to its use are analysed. The requirements of the users of ERDS are then investigated , and the basic archi tecture of an intelligent interface is illustrated. The design c r iteria of the two main modules of the i nterface , name ly the natural language query interface and the expert interface , are later discussed. At last , the present state of t h e project is reported and promising directi o ns for future research are out1 ined .

In distributed data environments, peers (data sources) are connected with each other through a set of semantic correspondences in such a way that peers directly connected are called semantic neighbours. Queries are submitted considering partial information provided by a peer schema and may be answered by other neighbour peers. From the query submission peer, the original query is successively rewritten into queries over the peers, according to the correspondences between the original peer and the target ones. In this process, some of the original query terms may be lost while other ones may be added, leading to a semantic loss of the original query. In this work, we argue that it is essential to try preserving the original query semantics if we wish to hold what the users defined as important at query submission time. With this in mind, we propose an approach to preserve the original query semantics in query routing processes. Furthermore, we present a metric for assessing the relevance of neighbour peers according to an estimated query semantic value obtained at each query reformulation. In this paper, we present the developed approach and some experimental results we have accomplished.

Dynamic environments are descentralized systems that provide users with querying capabilities over a set of heterogeneous, distributed and autonomous data sources. Data Integration Systems, Peer Data Management Systems (PDMS) and Dataspaces are examples of such systems. They are composed by data sources (peers) that belong to a specific domain and are linked to each other by mappings (correspondences). Nonetheless, a challenge inherent to dynamic environments is to analyze the semantic loss during query reformulation. A semantic loss may occur when a query is reformulated from a peer to another in the system. To minimize the consequences of this problem, we propose the use of information quality criteria to help the semantic loss analysis. The semantic loss analysis is a step executed to verify the query routing possibilities.

Query formulation and reformulation is recognized as one of the most difficult tasks that users in information retrieval systems are asked to perform. This study investigated the use of two different techniques for supporting query reformulation in interactive information retrieval: relevance feedback and Local Context Analysis, both implemented as term−suggestion devices. The former represents techniques which offer user control and understanding of term suggestion; the latter represents techniques which require relatively little user effort. Using the TREC−8 Interactive Track task and experimental protocol, we found that although there were no significant differences between two systems implementing these techniques in terms of user preference and performance in the task, subjects using the Local Context Analysis system had significantly fewer user−defined query terms than those in the relevance feedback system. We conclude that term suggestion without user guidance/control is the better of the two methods tested, for this task, since it required less effort for the same level of performance. We also found that both number of documents saved and number of instances identified by subjects were significantly correlated with the criterion measures of instance recall and precision, and conclude that this suggests that it is not necessary to rely on external evaluators for measurement of performance of interactive information retrieval in the instance identification task.

Search engine logs store detailed information on Web users interactions. Thus, as more and more people use search engines on a daily basis, important trails of users common knowledge are being recorded in those files. Previous research has shown that it is possible to extract concept taxonomies from full text documents, while other scholars have proposed methods to obtain similar queries from query logs. We propose a mixture of both lines of research, that is, mining query logs not to find related queries nor query hierarchies, but actual term taxonomies that could be used to improve search engine effectiveness and efficiency. As a result, in this study we have developed a method that combines lexical heuristics with a supervised classification model to successfully extract hyponymy relations from specialization search patterns revealed from log missions, with no additional sources of information, and in a language independent way.

Success of query reformulation and relevant information retrieval depends on many factors, such as users' prior knowledge, age, gender, and cognitive styles. One of the important factors that affect a user's query reformulation behaviour is that of the nature of the search tasks. Limited studies have examined the impact of the search task types on query reformulation behaviour while performing Web searches. This paper examines how the nature of the search tasks affects users' query reformulation behaviour during information searching. The paper reports empirical results from a user study in which 50 participants performed a set of three Web search tasks-exploratory, factorial and abstract. Users' interactions with search engines were logged by using a monitoring program. 872 unique search queries were classified into five query types-New, Add, Remove, Replace and Repeat. Users submitted fewer queries for the factual task, which accounted for 26%. They completed a higher number of queries (40% of the total queries) while carrying out the exploratory task. A one-way MANOVA test indicated a significant effect of search task types on users' query reformulation behaviour. In particular, the search task types influenced the manner in which users reformulated the New and Repeat queries.

Success of query reformulation and relevant information retrieval depends on many factors, such as users' prior knowledge, age, gender, and cognitive styles. One of the important factors that affect a user's query reformulation behaviour is that of the nature of the search tasks. Limited studies have examined the impact of the search task types on query reformulation behaviour while performing Web searches. This paper examines how the nature of the search tasks affects users' query reformulation behaviour during information searching. The paper reports empirical results from a user study in which 50 participants performed a set of three Web search tasks-exploratory, factorial and abstract. Users' interactions with search engines were logged by using a monitoring program. 872 unique search queries were classified into five query types-New, Add, Remove, Replace and Repeat. Users submitted fewer queries for the factual task, which accounted for 26%. They completed a higher number of queries (40% of the total queries) while carrying out the exploratory task. A one-way MANOVA test indicated a significant effect of search task types on users' query reformulation behaviour. In particular, the search task types influenced the manner in which users reformulated the New and Repeat queries.

InOrder is a query refinement tool that works on top of Goolge and helps individual users to collaboratively participate in best Web query formulations. The incremental refinement works via an indirect communication process facilitated by a visual interface which adapts significantly to reflect user contributions. The interface visually guides users in an implicit manner via a “what you click is what you mean" approach which assists semantic visualization of past interactions by highlighting relevant search terms in brighter colors. Users simply click on anything that seems relevant while being ‘attracted’ to the terms already clicked by other users. This elicits conceptual refinements and reduces the rating effort required by many collaborative systems. InOrder functions as a "visual search WIKI", which represents search intent rather than search of formal articles. Since it takes less effort to click than type, the system increases search usability by reducing the i...

lyon1.fr Résumé. Le développement du Web Sémantique a conduità l'élaboration de standards pour la représentation des connaissances sur le Web. RDF, comme un de ces standards, est devenu une recommandation du W3C. Même s'il aété conçu pourêtre interprétable par l'homme et la machine (encodage XML, triplets, graphesétiquetés), RDF n'a pasété fourni avec des services d'interrogation et de raisonnement. La plupart des travaux concernant l'interrogation de documents RDF se sont concentrés sur l'usage de techniques issues de la programmation logique et sur des extensions de SQL. Nous portons un nouveau regard sur les techniques d'interrogation et de raisonnement sur les documents RDF et nous montrons que la sémantique des termes OSF (Order Sorted Features) est compatible avec la représentation isomorphique (triplets) des propositions RDF. Cette transformation permet l'ordonnancement des ressources en ontologies et, a travers ceci, des meilleurs mécanismes de réponses (par approximation et recouvrement) aux interrogations de documents RDF.

lyon1.fr Résumé. Le développement du Web Sémantique a conduità l'élaboration de standards pour la représentation des connaissances sur le Web. RDF, comme un de ces standards, est devenu une recommandation du W3C. Même s'il aété conçu pourêtre interprétable par l'homme et la machine (encodage XML, triplets, graphesétiquetés), RDF n'a pasété fourni avec des services d'interrogation et de raisonnement. La plupart des travaux concernant l'interrogation de documents RDF se sont concentrés sur l'usage de techniques issues de la programmation logique et sur des extensions de SQL. Nous portons un nouveau regard sur les techniques d'interrogation et de raisonnement sur les documents RDF et nous montrons que la sémantique des termes OSF (Order Sorted Features) est compatible avec la représentation isomorphique (triplets) des propositions RDF. Cette transformation permet l'ordonnancement des ressources en ontologies et, a travers ceci, des meilleurs mécanismes de réponses (par approximation et recouvrement) aux interrogations de documents RDF.