Interactive Retrieval Based on Wikipedia Concepts
Lanbo Zhang
TL;DR
This paper introduces a novel interactive retrieval approach leveraging Wikipedia concepts, allowing users to refine searches effectively, with methods evaluated on TREC datasets showing significant performance improvements.
Contribution
It proposes new methods for selecting relevant Wikipedia concepts and re-ranking documents based on user feedback, enhancing retrieval effectiveness.
Findings
Methods significantly improve retrieval performance on TREC datasets.
User feedback on Wikipedia concepts effectively refines search results.
The approach outperforms traditional retrieval methods.
Abstract
This paper presents a new user feedback mechanism based on Wikipedia concepts for interactive retrieval. In this mechanism, the system presents to the user a group of Wikipedia concepts, and the user can choose those relevant to refine his/her query. To realize this mechanism, we propose methods to address two problems: 1) how to select a small number of possibly relevant Wikipedia concepts to show the user, and 2) how to re-rank retrieved documents given the user-identified Wikipedia concepts. Our methods are evaluated on three TREC data sets. The experiment results show that our methods can dramatically improve retrieval performances.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsTopic Modeling · Information Retrieval and Search Behavior · Web Data Mining and Analysis