A graph-based recommender system for digital library
Proceedings of the 2nd ACM/IEEE-CS joint conference on Digital libraries
A survey on the use of relevance feedback for information access systems
The Knowledge Engineering Review
ACM SIGIR Forum
ESTER: efficient search on text, entities, and relations
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Ranking very many typed entities on wikipedia
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
EntityRank: searching entities directly and holistically
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
A simple and efficient sampling method for estimating AP and NDCG
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Combining document- and paragraph-based entity ranking
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Inferring the most important types of a query: a semantic approach
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Overview of the INEX 2007 Entity Ranking Track
Focused Access to XML Documents
Structured Document Retrieval, Multimedia Retrieval, and Entity Ranking Using PF/Tijah
Focused Access to XML Documents
Exploiting locality of Wikipedia links in entity ranking
ECIR'08 Proceedings of the IR research, 30th European conference on Advances in information retrieval
Entity summarization of news articles
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Why finding entities in Wikipedia is difficult, sometimes
Information Retrieval
Category-based query modeling for entity search
ECIR'2010 Proceedings of the 32nd European conference on Advances in Information Retrieval
An exploration of ranking models and feedback method for related entity finding
Information Processing and Management: an International Journal
| Hi-index | 0.00 |
Web search increasingly deals with structured data about people, places and things, their attributes and relationships. In such an environment an important sub-problem is matching a user's unstructured free-text query to a set of relevant entities. For example, a user might request 'Olympic host cities'. The most challenging general problem is to find relevant entities, of the correct type and characteristics, based on a free-text query that need not conform to any single ontology or category structure. This paper presents an entity ranking relevance feedback model, based on example entities specified by the user or on pseudo feedback. It employs the Wikipedia category structure, but augments that structure with 'smooth categories' to deal with the sparseness of the raw category information. Our experiments show the effectiveness of the proposed method, whether applied as a pseudo relevance feedback method or interactively with the user in the loop.