OHSUMED: an interactive retrieval evaluation and new large test collection for research
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Aspect windows, 3-D visualizations, and indirect comparisons of information retrieval systems
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
The use of MMR, diversity-based reranking for reordering documents and producing summaries
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
A vector space model for automatic indexing
Communications of the ACM
Information Retrieval
ICADL '02 Proceedings of the 5th International Conference on Asian Digital Libraries: Digital Libraries: People, Knowledge, and Technology
Beyond independent relevance: methods and evaluation metrics for subtopic retrieval
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Lexical cohesion computed by thesaural relations as an indicator of the structure of text
Computational Linguistics
Affinity rank: a new scheme for efficient web search
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
Concept-based document readability in domain specific information retrieval
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Ontology selection for the real semantic web: how to cover the queen's birthday dinner?
EKAW'06 Proceedings of the 15th international conference on Managing Knowledge in a World of Networks
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The increased variety of information makes it critical to retrieve documents which are not only relevant but also broad enough to cover as many different aspects of a certain topic as possible. The increased variety of users also makes it critical to retrieve documents that are jargon free and easy-to-understand rather than the specific technical materials. In this paper, we propose a new concept namely document generality computation. Generality of document is of fundamental importance to information retrieval. Document generality is the state or quality of document being general. We compute document generality based on a domain-ontology method that analyzes scope and semantic cohesion of concepts appeared in the text. For test purposes, our proposed approach is then applied to improving the performance of document ranking in bio-medical information retrieval. The retrieved documents are re-ranked by a combined score of similarity and the closeness of documents' generality to that of a query. The experiments have shown that our method can work on a large scale bio-medical text corpus OHSUMED (Hersh, Buckley, Leone & Hickam 1994), which is a subset of MED-LINE collection containing of 348,566 medical journal references and 101 test queries, with an encouraging performance.