Query Reformulation in Collaborative Information Retrieval

Traditionally information retrieval (IR) research has focussed on a single user interaction modality, where a user searches to satisfy an information need. Recent advances in both web technologies, such as the sociable web of Web 2.0, and computer hardware, such as tabletop interface devices, have enabled multiple users to collaborate on many computer-related tasks. Due to these advances there is an increasing need to support two or more users searching together at the same time, in order to satisfy a shared information need, which we refer to as Synchronous Collaborative Information Retrieval.

2009

Synchronous Collaborative Information Retrieval refers to systems that support multiple users searching together at the same time in order to satisfy a shared information need. To date most SCIR systems have focussed on providing various awareness tools in order to enable collaborating users to coordinate the search task. However, requiring users to both search and coordinate the group activity may prove too demanding. On the other hand without effective coordination policies the group search may not be effective. In this paper we propose and evaluate novel system-mediated techniques for coordinating a group search. These techniques allow for an effective division of labour across the group whereby each group member can explore a subset of the search space. We also propose and evaluate techniques to support automated sharing of knowledge across searchers in SCIR, through novel collaborative and complementary relevance feedback techniques. In order to evaluate these techniques, we propose a framework for SCIR evaluation based on simulations. To populate these simulations we extract data from TREC interactive search logs. This work represent the first simulations of SCIR to date and the first such use of this TREC data.

2008

Users enter queries that are short as well as long. The aim of this work is to evaluate techniques that can enable information retrieval (IR) systems to automatically adapt to perform better on such queries. By adaptation we refer to (1) modifications to the queries via user interaction, and (2) detecting that the original query is not a good candidate for modification.

We propose to extend standard information retrieval (IR) ad-hoc test collection design to facilitate research on personalized and collaborative IR by gathering additional meta-information during the topic (query) development process. We propose a controlled query generation process with activity logging for each topic developer. The standard ad-hoc collection will thus be accompanied by a new set of thematically related topics and the associated log information, and has the potential to simulate a real-world search scenario to encourage retrieval systems to mine user information from the logs to improve IR effectiveness. The proposed methodology described in this paper will be applied in a pilot task which is scheduled to run in the FIRE 2011 evaluation campaign. The task aims at investigating the research question of whether personalized and collaborative IR retrieval experiments and evaluation can be pursued by enriching a standard ad-hoc collection with such meta-information.

2004

Abstract. Search engines are the primary means by which people locate information on the Web. Unfortunately most Web users are not information retrieval experts and there is a tendency for Web queries to be ambiguous and under-specified. Query expansion and recommendation techniques offer one way to solve the ambiguous query problem in Web search, by automatically identifying and adding new terms to a vague query in order to focus the search.

2006

Synchronous Collaborative Information Retrieval refers to systems that support multiple users searching together at the same time in order to satisfy a shared information need. To date most SCIR systems have focussed on providing various awareness tools in order to enable collaborating users to coordinate the search task. However, requiring users to both search and coordinate the group activity may prove too demanding. On the other hand without effective coordination policies the group search may not be effective. In this paper we propose and evaluate novel system-mediated techniques for coordinating a group search. These techniques allow for an effective division of labour across the group whereby each group member can explore a subset of the search space. We also propose and evaluate techniques to support automated sharing of knowledge across searchers in SCIR, through novel collaborative and complementary relevance feedback techniques. In order to evaluate these techniques, we propose a framework for SCIR evaluation based on simulations. To populate these simulations we extract data from TREC interactive search logs. This work represent the first simulations of SCIR to date and the first such use of this TREC data.

Abstract Information retrieval (IR) tools are engaged to find information in electronic form, in databases, digital libraries, and networks. However, the advent of the web technology has boosted the amount of information available to us way beyond our cognitive capacity. The importance of good IR tools has thus increased and the tools have become natural focal points for organisational information seeking. This situation offers a possibility to exploit the collaborative efforts of the individual users. However, is the opportunity utilised?

Proceedings of the Second International Conference on Software and Data Technologies, 2007

This paper introduces a new approach of query reuse in order to help the user to retrieve relevant information. Past search experiences are a source of information that can be useful for a user trying to find information answering his information need. For example, a user searching about a new subject can benefit from past search experiences carried out by previous users about the same subject. The approach presented in this paper is based on collecting the different search attempts submitted to a search engine by a user trying to fulfil an information need. This approach takes mainly advantage of implicit links that exist between the different search attempts that try to satisfy a single information need. Search experiences are modelled according to the concepts defined in the domain of version management. This modelling provides multiple possibilities to reuse past experiences notably to recommend terms for query reformulation or documents judged relevant by other users.

Information Processing & Management, 2005

In this article we investigate the expressions of collaborative activities within information seeking and retrieval processes (IS&R). Generally, information seeking and retrieval is regarded as an individual and isolated process in IR research. We assume that an IS&R situation is not merely an individual effort, but inherently involves various collaborative activities. We present empirical results from a real-life and information-intensive setting within the patent domain, showing that the patent task performance process involves highly collaborative aspects throughout the stages of the information seeking and retrieval process. Furthermore, we show that these activities may be categorised and related to different stages in an information seeking and retrieval process. Therefore, the assumption that information retrieval performance is purely individual needs to be reconsidered. Finally, we also propose a refined IR framework involving collaborative aspects.

Web information is too heterogeneous that users have difficulties to retrieve their needed information: text, image or video. In this context, the collaborative work presents one solution proposed to solve this problem. Collaborative retrieval enables the retrieval histories' sharing between users having the same profile across multiple tools such as annotations. We propose in this paper to improve collaborative retrieval performance, considering the annotations as a new source of information describing documents. In our contribution, we propose to apply the relevance feedback to extend the user's query. So we use a possibilistic approach to extract the relevant terms from annotations given in semi-structured documents returned by collaborative retrieval systems.