Viewing morphology as an inference process
SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Relevance based language models
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Bursty and hierarchical structure in streams
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Language Modeling for Information Retrieval
Language Modeling for Information Retrieval
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Ranking robustness: a novel framework to predict query performance
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
ACM Transactions on Information Systems (TOIS)
Performance prediction using spatial autocorrelation
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Measuring ranked list robustness for query performance prediction
Knowledge and Information Systems
Improved query difficulty prediction for the web
Proceedings of the 17th ACM conference on Information and knowledge management
Event detection with common user interests
Proceedings of the 10th ACM workshop on Web information and data management
Integration of news content into web results
Proceedings of the Second ACM International Conference on Web Search and Data Mining
Proceedings of the Second ACM International Conference on Web Search and Data Mining
Improving search relevance for implicitly temporal queries
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Search result re-ranking by feedback control adjustment for time-sensitive query
NAACL-Short '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers
Predicting Neighbor Goodness in Collaborative Filtering
FQAS '09 Proceedings of the 8th International Conference on Flexible Query Answering Systems
Leveraging temporal dynamics of document content in relevance ranking
Proceedings of the third ACM international conference on Web search and data mining
Temporal query log profiling to improve web search ranking
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Detecting periodic changes in search intentions in a search engine
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Determining time of queries for re-ranking search results
ECDL'10 Proceedings of the 14th European conference on Research and advanced technology for digital libraries
Understanding temporal query dynamics
Proceedings of the fourth ACM international conference on Web search and data mining
Ranking related news predictions
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
A comparison of time-aware ranking methods
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Efficient query evaluation through access-reordering
AIRS'06 Proceedings of the Third Asia conference on Information Retrieval Technology
A performance prediction approach to enhance collaborative filtering performance
ECIR'2010 Proceedings of the 32nd European conference on Advances in Information Retrieval
Using query profiles for clarification
ECIR'06 Proceedings of the 28th European conference on Advances in Information Retrieval
Automatic refinement of patent queries using concept importance predictors
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Improving retrieval of short texts through document expansion
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Labeling documents with timestamps: learning from their time expressions
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
Learning to rank search results for time-sensitive queries
Proceedings of the 21st ACM international conference on Information and knowledge management
Temporal models for microblogs
Proceedings of the 21st ACM international conference on Information and knowledge management
Modeling geographic, temporal, and proximity contexts for improving geotemporal search
Journal of the American Society for Information Science and Technology
Numeric query ranking approach
Proceedings of the 22nd international conference on World Wide Web companion
Predicting event-relatedness of popular queries
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Exploiting temporal information in Web search
Expert Systems with Applications: An International Journal
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A key missing component in information retrieval systems is self-diagnostic tests to establish whether the system can provide reasonable results for a given query on a document collection. If we can measure properties of a retrieved set of documents which allow us to predict average precision, we can automate the decision of whether to elicit relevance feedback, or modify the retrieval system in other ways. We use meta-data attached to documents in the form of time stamps to measure the distribution of documents retrieved in response to a query, over the time domain, to create a temporal profile for a query. We define some useful features over this temporal profile. We find that using these temporal features, together with the content of the documents retrieved, we can improve the prediction of average precision for a query.