C4.5: programs for machine learning
C4.5: programs for machine learning
Machine Learning
An algorithm for suffix stripping
Readings in information retrieval
User interactions with everyday applications as context for just-in-time information access
Proceedings of the 5th international conference on Intelligent user interfaces
Communications of the ACM
Communications of the ACM
Ensembling neural networks: many could be better than all
Artificial Intelligence
The Alternating Decision Tree Learning Algorithm
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
Case Representation Issues for Case-Based Reasoning from Ensemble Research
ICCBR '01 Proceedings of the 4th International Conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
A decision-theoretic generalization of on-line learning and an application to boosting
EuroCOLT '95 Proceedings of the Second European Conference on Computational Learning Theory
EMCL '01 Proceedings of the 12th European Conference on Machine Learning
The Use of Implicit Evidence for Relevance Feedback in Web Retrieval
Proceedings of the 24th BCS-IRSG European Colloquium on IR Research: Advances in Information Retrieval
Improving Category Specific Web Search by Learning Query Modifications
SAINT '01 Proceedings of the 2001 Symposium on Applications and the Internet (SAINT 2001)
Personalized Web Search For Improving Retrieval Effectiveness
IEEE Transactions on Knowledge and Data Engineering
Exploiting Query Repetition and Regularity in an Adaptive Community-Based Web Search Engine
User Modeling and User-Adapted Interaction
Personalizing search via automated analysis of interests and activities
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Letizia: an agent that assists web browsing
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
A live-user evaluation of collaborative web search
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Selective ensemble of decision trees
RSFDGrC'03 Proceedings of the 9th international conference on Rough sets, fuzzy sets, data mining, and granular computing
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Query recommendation using query logs in search engines
EDBT'04 Proceedings of the 2004 international conference on Current Trends in Database Technology
Decision Templates Based RBF Network for Tree-Structured Multiple Classifier Fusion
MCS '09 Proceedings of the 8th International Workshop on Multiple Classifier Systems
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Collaborative Web Search (CWS) is a technique used to re-rank the results of Web search engines to reflect the collective preferences of a community of online searchers. It applies a case-based reasoning perspective to Web search. In simple terms, past search sessions (queries and result selections) are stored as search cases and reused in response to similar queries; previously selected results, which have been regularly selected for similar queries in the past, are promoted in response to the new query. One of the limitations of CWS is that it only facilitates the promotion of previously selected results. In this paper we propose a solution by adopting a different type of case representation in which a search session is represented by a relevance model (e.g., a decision tree) learned from the selections made during the session. Each new target query results in the retrieval of a set of similar search cases and their component decision trees are dynamically combined to produce an ensemble classifier that is then used to re-rank the result-list to promote community-relevant results. We present the results of an evaluation based on live-user searching histories and show that this ensemble-based approach can outperform a standard CWS system.