Analysis of topic dynamics in web search
WWW '05 Special interest tracks and posters of the 14th international conference on World Wide Web
Web search personalization with ontological user profiles
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Concept-based feature generation and selection for information retrieval
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
Concept-Based, Personalized Web Information Gathering: A Survey
KSEM '09 Proceedings of the 3rd International Conference on Knowledge Science, Engineering and Management
Representing context in web search with ontological user profiles
CONTEXT'07 Proceedings of the 6th international and interdisciplinary conference on Modeling and using context
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part I
Exploiting the category structure of Wikipedia for entity ranking
Artificial Intelligence
Graph-based concept weighting for medical information retrieval
Proceedings of the Seventeenth Australasian Document Computing Symposium
| Hi-index | 0.00 |
As the number of available Web pages grows, users experience increasing difficulty finding documents relevant to their interests. One of the underlying reasons for this is that most search engines find matches based on keywords, regardless of their meanings. To provide the user with more useful information, we need a system that disambiguates queries by including information about the user's conceptual framework. This is the goal of KeyConcept, a conceptual search engine. During indexing, KeyConcept automatically classifies documents into concepts selected from a reference concept hierarchy. During retrieval, KeyConcept ranks documents based on a combination of keyword and conceptual similarity. This paper describes the system architecture and discusses the results of experiments that evaluate the effect of exploiting the hierarchical relationships between concepts during retrieval. Our results confirm that conceptual match significantly improves the precision of the search results over keyword match alone. In addition, the use of the concept hierarchy to prune irrelevant search results also significantly increases precision.