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WWW7 Proceedings of the seventh international conference on World Wide Web 7
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
Wrapper induction: efficiency and expressiveness
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Knowledge-based extraction of named entities
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Building Light-Weight Wrappers for Legacy Web Data-Sources Using W4F
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Mining data records in Web pages
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Hybrid XML Retrieval: Combining Information Retrieval and a Native XML Database
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GATE: an architecture for development of robust HLT applications
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Entity extraction without language-specific resources
COLING-02 proceedings of the 6th conference on Natural language learning - Volume 20
TREC: Experiment and Evaluation in Information Retrieval (Digital Libraries and Electronic Publishing)
ACM SIGIR Forum
Ontology evaluation using wikipedia categories for browsing
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Wrapper maintenance: a machine learning approach
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Ontology-driven automatic entity disambiguation in unstructured text
ISWC'06 Proceedings of the 5th international conference on The Semantic Web
Using Wikipedia Categories and Links in Entity Ranking
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International Journal of Human-Computer Studies
Annotating wikipedia articles with semantic tags for structured retrieval
Proceedings of the 2nd ACM workshop on Social web search and mining
Entity ranking using Wikipedia as a pivot
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
TAER: time-aware entity retrieval-exploiting the past to find relevant entities in news articles
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Entity-relationship queries over wikipedia
SMUC '10 Proceedings of the 2nd international workshop on Search and mining user-generated contents
Entity ranking in Wikipedia: utilising categories, links and topic difficulty prediction
Information Retrieval
Ranking entities using web search query logs
ECDL'10 Proceedings of the 14th European conference on Research and advanced technology for digital libraries
RIAO '10 Adaptivity, Personalization and Fusion of Heterogeneous Information
Query modeling for entity search based on terms, categories, and examples
ACM Transactions on Information Systems (TOIS)
Linking FRBR entities to LOD through semantic matching
TPDL'11 Proceedings of the 15th international conference on Theory and practice of digital libraries: research and advanced technology for digital libraries
SISP: a new framework for searching the informative subgraph based on PSO
Proceedings of the 20th ACM international conference on Information and knowledge management
Category-based query modeling for entity search
ECIR'2010 Proceedings of the 32nd European conference on Advances in Information Retrieval
Entity-Relationship Queries over Wikipedia
ACM Transactions on Intelligent Systems and Technology (TIST)
Exploiting the category structure of Wikipedia for entity ranking
Artificial Intelligence
ISWC'12 Proceedings of the 11th international conference on The Semantic Web - Volume Part I
Towards an enhanced and adaptable ontology by distilling and assembling online encyclopedias
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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The traditional entity extraction problem lies in the ability of extracting named entities from plain text using natural language processing techniques and intensive training from large document collections. Examples of named entities include organisations, people, locations, or dates. There are many research activities involving named entities; we are interested in entity ranking in the field of information retrieval. In this paper, we describe our approach to identifying and ranking entities from the INEX Wikipedia document collection. Wikipedia offers a number of interesting features for entity identification and ranking that we first introduce. We then describe the principles and the architecture of our entity ranking system, and introduce our methodology for evaluation. Our preliminary results show that the use of categories and the link structure of Wikipedia, together with entity examples, can significantly improve retrieval effectiveness.