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Outline

Title
Abstract
Overview of Web Information Systems
Data
Methodological Foundations
Systems Analysis and Design
Is Analysis and Design
Integrated Database Schema and View Derivation
Connoisseur Database Schema
Gourmet Database Schema
Resume and Future Work
The Data Type Layer
The Database Type Layer
Database Types and Data Types
Data Types
Database Types
Database Schemata and Databases
Data Representation
Authorization Subjects and Objects
Related Work
Conclusion and Future Work
Background
Illustrative Case Study
Resulting Materialized Ontology View
Objectives
Data Extraction Language
Crawl Related Features
Data Extraction Rules
Data Extraction Schema
Wiccap Data Model
Summary of Wiccap
Classifier Fusion: Methods and Systems
Fusion Methods
Overview of the X-Device System
Finding Homogeneous Classifiers
Conclusion and Future Trends
Analysis of Web Access Logs
Review of Existing Indexing Techniques
Family of Sequence Indexing Methods
Results with Synthetic Data
Results with Real Data
Future Trends
Introduction
Web Usage Data
Web Log Data Set
Method
Summary
Pattern Analysis and Applications
Conclusion
References

Web Information Extraction via Web Views

Profile image of Ee-Peng LIMEe-Peng LIM

2004

Abstract

ABSTRACT With the explosion of information on the Web, traditional ways of browsing and keyword searching of information over web pages no longer satisfy the demanding needs of web surfers. Web information extraction has emerged as an important research area that aims to automatically extract information from target web pages and convert them into a structured format for further processing.

Related papers

Web Data Extraction, Applications and Techniques: A Survey
linda wijaya

The World Wide Web contains a huge amount of unstructured and semi-structured information, that is exponentially increasing with the coming of the Web 2.0, thanks to User-Generated Contents (UGC). In this paper we intend to briefly survey the fields of application, in particular enterprise and social applications, and techniques used to approach and solve the problem of the extraction of information from Web sources: during last years many approaches were developed, some inherited from past studies on Information Extraction (IE) systems, many others studied ad hoc to solve specific problems.

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HWPDE: Novel Approach for Data Extraction from Structured Web Pages
Manpreet Sehgal

2013

Diving into the World Wide Web for the purpose of fetching precious stones (relevant information) is a tedious task under the limitations of current diving equipments (Current Browsers). While a lot of work is being carried out to improve the quality of diving equipments, a related area of research is to devise a novel approach for mining. This paper describes a novel approach to extract the web data from the hidden websites so that it can be used as a free service to a user for a better and improved experience of searching relevant data. Through the proposed method, relevant data (Information) contained in the web pages of hidden websites is extracted by the crawler and stored in the local database so as to build a large repository of structured and indexed and ultimately relevant data. Such kind of extracted data has a potential to optimally satisfy the relevant Information starving end user.

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Automatic Extraction of Complex Web Data
Jon Patrick

PACIS 2006 Proceedings, 2006

A new wrapper induction algorithm WTM for generating rules that describe the general web page layout template is presented. WTM is mainly designed for use in weblog crawling and indexing system. Most weblogs are maintained by content management systems and have similar layout structures in all pages. In addition, they provide RSS feeds to describe the latest entries. These entries appear in the weblog homepage in HTML format as well. WTM is built upon these two observations. It uses RSS feed data to automatically label the corresponding HTML file (weblog homepage) and induces general template rules from the labeled page. The rules can then be used to extract data from other pages of similar layout template. WTM is tested on some selected weblogs and the results are satisfactory.

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Building Web Information Extraction Tasks
Benjamin Habegger

2004

Most recent research in the field of information extraction from the Web has concentrated on the task of extracting the underlying content of a set of similarly structured web pages. However in order to build real-world web information extraction applications this is not sufficient. Indeed, building such applications requires fully automating the access to web sources. This does not just involve the extraction of the data from web pages. There is a need to set up the necessary infrastructure allowing to query a source, retrieve the result pages, extract the results from these pages and filter out the unwanted results. In this paper we show how such an infrastructure can be set up. We propose to build a web information extraction application by decomposing it into sub-tasks and describing it in an XML based language named WetDL. Each of the sub-tasks consists in applying a web information extraction specific operation onto its input, one of these operators being the application of an extractor. By connecting such operations together it is possible to simply define complex applications. This is shown in the paper by applying this approach to real-world information extraction tasks such as extracting DVD listings from Amazon.com, extracting addresses from online telephone directories superpages.com, etc.

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Roadrunner: Towards automatic data extraction from large web sites
Hrishikesh Rane

Proceedings of the international …, 2001

The paper investigates techniques for extracting data from HTML sites through the use of automatically generated wrappers. To automate the wrapper generation and the data extraction process, the paper develops a novel technique to compare HTML pages and generate a wrapper based on their similarities and differences. Experimental results on real-life data-intensive Web sites confirm the feasibility of the approach.

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Automatic information extraction from semi-structured Web pages by pattern discovery
Chun-Nan Hsu

Decision Support Systems, 2003

The World Wide Web is now undeniably the richest and most dense source of information; yet, its structure makes it difficult to make use of that information in a systematic way. This paper proposes a pattern discovery approach to the rapid generation of information extractors that can extract structured data from semi-structured Web documents. Previous work in wrapper induction aims at learning extraction rules from user-labeled training examples, which, however, can be expensive in some practical applications. In this paper, we introduce IEPAD (an acronym for Information Extraction based on PAttern Discovery), a system that discovers extraction patterns from Web pages without user-labeled examples. IEPAD applies several pattern discovery techniques, including PAT-trees, multiple string alignments and pattern matching algorithms. Extractors generated by IEPAD can be generalized over unseen pages from the same Web data source. We empirically evaluate the performance of IEPAD on an information extraction task from 14 real Web data sources. Experimental results show that with the extraction rules discovered from a single page, IEPAD achieves 96% average retrieval rate, and with less than five example pages, IEPAD achieves 100% retrieval rate for 10 of the sample Web data sources. D

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WetDL: A Web Information Extraction Language
Benjamin Habegger

2004

Many online information sources are available on the Web. Giving machine access to such sources leads to many interesting applications, such as using web data in mediators or software agents. Up to now most work in the field of information extraction from the web has concentrated on building wrappers, i.e. programs allowing to reformat presentational data in HTML into a more machine comprehensible format. While being an important part of a web information extraction application such wrappers are not sufficient to fully access a source. Indeed, it is necessary to setup an infrastructure allowing to build queries, fetch pages, extract specific links, etc. In this paper we propose a language called WetDL allowing to describe an information extraction task as a network of operators whose execution performs the desired extraction task.

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EXPERIENCES REGARDING AUTOMATIC DATA EXTRACTION FROM WEB PAGES
Mihai Gabroveanu

2006

Existing methods of information extraction from HTML documents include manual approach, supervised learning and automatic techniques. The manual method has high precision and recall values but it is difficult to apply it for large number of pages. Supervised learning involves human interaction to create positive and negative samples. Automatic techniques benefit from less human effort but they are not highly reliable regarding the information retrieved. Our experiments align in the area of this last type of methods for this purpose developing a tool for automatic data extraction from HTML pages.

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Trend of Supervised Web Data Extraction
Galih Hendro

2018

Website has evolved since it was first developed in 1990. Since then, the website grows rapidly. Based on the information provided by http://www.worldwidewebsize.com the number of websites is currently at least 4.54 billion pages. With a very large number, the website stores a lot of information that can be used. That problem brings up the concept of data extraction. Web data extraction aims to retrieve the contents of the website so that it can be easy to use for other purposes. The utilization of web data extraction can be used in a product catalog, news, bookstore, travel, etc. There are many systems build by different technique such as manual, supervised, un-supervised, and semi-supervised. This paper discuss supervised learning technique for web data extraction. Several previous surveys have overviewed the wrapper induction system using the concept of supervised techniques to extracted web data up to 2007. The aim of this paper is to present a comprehensive overview of the rese...

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Adaptive web information extraction
Dawn Gregg, Steven Walczak

Communications of the ACM, 2006

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  260. Massey University's Turitea campus in Palmerston North (New Zealand). She teaches the theory, principles and practice of banking at both the undergraduate and post-graduate levels. Her research interests include the interaction between banks and customers, bank distribution channels, and internet bank- ing. Robert Meersman was awarded a PhD in Mathematics at the Free University of Brussels (VUB) (Belgium) in 1976. He was appointed full professor at VUB in 1995. Earlier positions include the University of Antwerp (UIA, 1975-1978)
  261. and Control Data Corp. (Data Management Lab, Brussels, Belgium, 1978- 1983). There, he worked on the definition of the NIAM (now ORM) method, as well as on languages (RIDL) and the first tools for this methodology. He has held chairs and founded the InfoLabs at University of Limburg (Belgium, 1983- 1986) and at the University of Tilburg (The Netherlands, 1986-1995). Profes- sor Meersman was a member and past chairman (1983-1992) of the IFIP WG2.6 on Database, past chairman of the IFIP TC 12 (Artificial Intelligence, 1987-1992), co-founder and current president of the International Foundation for Cooperative Information Systems (IFCIS, since 1994) and of the Distrib- uted Objects Applications Institute (DOA, since 2000). He founded the Systems Technology and Applications Research Laboratory (STAR Lab) at VUB in 1995, and has been the director of STARLab since. His current scientific interests include ontologies, database semantics, domain and data- base modeling, interoperability and use of databases in applications such as enterprise knowledge management and the semantic web.
  262. Mikolaj Morzy is a research assistant at the Institute of Computing Science at Poznan University of Technology, Poland. He received his MSc in Comput- ing Science in 1998. Currently, he is working on a PhD concerning the integration of data mining techniques with database systems. His research interests include database systems, data warehouses and data mining. Tadeusz Morzy received his MSc, PhD, and Polish Habilitation from Poznan University of Technology, Poland. He is professor of Computer Science at the Institute of Computing Science, Poznan University of Technology. He has held visiting positions at Loyola University, New Orleans, USA; Klagenfurt Univer- sity, Austria; University La Sapienza, Italy; and the Polish-Japanese Institute of Information Technology, Warsaw, Poland. He has authored and co-authored more than 70 papers on databases, data mining, and data warehousing. He is co-author of a book on Concurrency Control in Distributed Database

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