A vector space model for automatic indexing
Communications of the ACM
A probabilistic model of information retrieval: development and comparative experiments Part 2
Information Processing and Management: an International Journal
Modern Information Retrieval
Document Ranking and the Vector-Space Model
IEEE Software
WWW '03 Proceedings of the 12th international conference on World Wide Web
Implementation of the SMART Information Retrieval System
Implementation of the SMART Information Retrieval System
Semantic similarity methods in wordNet and their application to information retrieval on the web
Proceedings of the 7th annual ACM international workshop on Web information and data management
An Adaptation of the Vector-Space Model for Ontology-Based Information Retrieval
IEEE Transactions on Knowledge and Data Engineering
Semantic annotation, indexing, and retrieval
Web Semantics: Science, Services and Agents on the World Wide Web
The impact of named entity normalization on information retrieval for question answering
ECIR'08 Proceedings of the IR research, 30th European conference on Advances in information retrieval
LRD: latent relation discovery for vector space expansion and information retrieval
WAIM '06 Proceedings of the 7th international conference on Advances in Web-Age Information Management
Ontology-based proximity search
Proceedings of the 13th International Conference on Information Integration and Web-based Applications and Services
Finding news story chains based on multi-dimensional event profiles
Proceedings of the 10th Conference on Open Research Areas in Information Retrieval
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Named entities have been considered and combined with keywords to enhance information retrieval performance. However, there is not yet a formal and complete model that takes into account entity names, classes, and identifiers together. Our work exploresvariousadaptations of the traditional Vector Space Model that combine different ontological features with keywords, and in different ways. It shows better performance of the proposed models as compared to the keyword-based Lucene, and their advantages for both text retrieval and representation of documents and queries.