A language modeling approach to information retrieval
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Condorcet fusion for improved retrieval
Proceedings of the eleventh international conference on Information and knowledge management
Combining document representations for known-item search
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
A study of smoothing methods for language models applied to information retrieval
ACM Transactions on Information Systems (TOIS)
Blog site search using resource selection
Proceedings of the 17th ACM conference on Information and knowledge management
It pays to be picky: an evaluation of thread retrieval in online forums
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Online community search using conversational structures
Information Retrieval
Data Fusion in Information Retrieval
Data Fusion in Information Retrieval
Using anchor text for homepage and topic distillation search tasks
Journal of the American Society for Information Science and Technology
| Hi-index | 0.00 |
Online forum thread retrieval is the task of retrieving threads that satisfy a user information need. Several thread representations have been proposed, and it has been found that combining these representations outperformed the retrieval using the individual representations. However, these combining methods leverage query relevance judgments to rank threads. Furthermore, in online forums, obtaining relevance judgments is not an option. As a result, in this paper, we propose to combine various thread representations using meta search techniques; many meta search techniques do not require training and has been found to produce a competitive result to the approaches that use relevance judgments. Our experimental result shows two things. First, combining thread representations using meta search techniques is an effective approach. Second, the CombSUM or the CombMNZ meta search techniques outperformed the best baseline method on high precision searches.