Language Modeling for Information Retrieval
Language Modeling for Information Retrieval
The Journal of Machine Learning Research
Image Retrieval Using Multiple Evidence Ranking
IEEE Transactions on Knowledge and Data Engineering
Automatic rule induction for unknown-word guessing
Computational Linguistics
Proceedings of the 6th ACM international conference on Image and video retrieval
Reranking Methods for Visual Search
IEEE MultiMedia
Proceedings of the 18th international conference on World wide web
HMNews: an integrated system for searching and browsing hypermedia news content
Proceedings of the 20th ACM conference on Hypertext and hypermedia
Measuring the descriptiveness of web comments
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Towards comment-based cross-media retrieval
Proceedings of the 19th international conference on World wide web
Learning to associate relevant photos to georeferenced textual documents
Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Information Retrieval in the Commentsphere
ACM Transactions on Intelligent Systems and Technology (TIST)
Multimedia Tools and Applications
Inter-media hashing for large-scale retrieval from heterogeneous data sources
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
Enhancing news organization for convenient retrieval and browsing
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
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We query the pictures of Yahoo! News for persons and objects by using the accompanying news captions as an indexing annotation. Our aim is to find these pictures on top of the answer list in which the sought persons or objects are most prominently present. We demonstrate that an appearance or content model based on syntactic, semantic and discourse analysis of the short news text is only useful for finding the best picture of a person of object if the database contains photos each picturing many entities. In other circumstances a simpler bag-of-nouns representation has a good performance. The appearance models are tested in a probabilistic ranking function.