Searching distributed collections with inference networks
SIGIR '95 Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval
An algorithm for suffix stripping
Readings in information retrieval
Cluster-based language models for distributed retrieval
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
GlOSS: text-source discovery over the Internet
ACM Transactions on Database Systems (TODS)
Query-based sampling of text databases
ACM Transactions on Information Systems (TOIS)
Query clustering using content words and user feedback
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
A language modeling framework for resource selection and results merging
Proceedings of the eleventh international conference on Information and knowledge management
Relevant document distribution estimation method for resource selection
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Unified utility maximization framework for resource selection
Proceedings of the thirteenth ACM international conference on Information and knowledge management
A Markov random field model for term dependencies
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Improving Automatic Query Classification via Semi-Supervised Learning
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
KDD CUP-2005 report: facing a great challenge
ACM SIGKDD Explorations Newsletter
Q2C@UST: our winning solution to query classification in KDDCUP 2005
ACM SIGKDD Explorations Newsletter
Building bridges for web query classification
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Distributed search over the hidden web: hierarchical database sampling and selection
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Learning query intent from regularized click graphs
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Blog site search using resource selection
Proceedings of the 17th ACM conference on Information and knowledge management
Integration of news content into web results
Proceedings of the Second ACM International Conference on Web Search and Data Mining
Sources of evidence for vertical selection
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Adaptation of offline vertical selection predictions in the presence of user feedback
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
SUSHI: scoring scaled samples for server selection
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Central-rank-based collection selection in uncooperative distributed information retrieval
ECIR'07 Proceedings of the 29th European conference on IR research
Sample sizes for query probing in uncooperative distributed information retrieval
APWeb'06 Proceedings of the 8th Asia-Pacific Web conference on Frontiers of WWW Research and Development
Ranking using multiple document types in desktop search
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
A joint probabilistic classification model for resource selection
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Vertical selection in the presence of unlabeled verticals
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Document allocation policies for selective searching of distributed indexes
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Foundations and Trends in Information Retrieval
Integrating explicit semantic analysis for ontology-based resource selection
Proceedings of the 13th International Conference on Information Integration and Web-based Applications and Services
Which should we try first? ranking information resources through query classification
FQAS'11 Proceedings of the 9th international conference on Flexible Query Answering Systems
Mixture model with multiple centralized retrieval algorithms for result merging in federated search
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Unsupervised linear score normalization revisited
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Shard ranking and cutoff estimation for topically partitioned collections
Proceedings of the 21st ACM international conference on Information and knowledge management
Reducing the uncertainty in resource selection
ECIR'13 Proceedings of the 35th European conference on Advances in Information Retrieval
Snippet-Based relevance predictions for federated web search
ECIR'13 Proceedings of the 35th European conference on Advances in Information Retrieval
ECIR'13 Proceedings of the 35th European conference on Advances in Information Retrieval
Distributed information retrieval and applications
ECIR'13 Proceedings of the 35th European conference on Advances in Information Retrieval
Taily: shard selection using the tail of score distributions
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Search result diversification in resource selection for federated search
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
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In some retrieval situations, a system must search across multiple collections. This task, referred to as federated search, occurs for example when searching a distributed index or aggregating content for web search. Resource selection refers to the subtask of deciding, given a query, which collections to search. Most existing resource selection methods rely on evidence found in collection content. We present an approach to resource selection that combines multiple sources of evidence to inform the selection decision. We derive evidence from three different sources: collection documents, the topic of the query, and query click-through data. We combine this evidence by treating resource selection as a multiclass machine learning problem. Although machine learned approaches often require large amounts of manually generated training data, we present a method for using automatically generated training data. We make use of and compare against prior resource selection work and evaluate across three experimental testbeds.