Probabilistic models in information retrieval
The Computer Journal - Special issue on information retrieval
Some simple effective approximations to the 2-Poisson model for probabilistic weighted retrieval
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
A probabilistic model of information retrieval: development and comparative experiments Part 2
Information Processing and Management: an International Journal
The SMART Retrieval System—Experiments in Automatic Document Processing
The SMART Retrieval System—Experiments in Automatic Document Processing
Large-Scale Concept Ontology for Multimedia
IEEE MultiMedia
The challenge problem for automated detection of 101 semantic concepts in multimedia
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
Towards optimal bag-of-features for object categorization and semantic video retrieval
Proceedings of the 6th ACM international conference on Image and video retrieval
A review of text and image retrieval approaches for broadcast news video
Information Retrieval
Semantic concept-based query expansion and re-ranking for multimedia retrieval
Proceedings of the 15th international conference on Multimedia
A probabilistic ranking framework using unobservable binary events for video search
CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
Assessing concept selection for video retrieval
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
Using high-level semantic features in video retrieval
CIVR'06 Proceedings of the 5th international conference on Image and Video Retrieval
Using query profiles for clarification
ECIR'06 Proceedings of the 28th European conference on Advances in Information Retrieval
Can High-Level Concepts Fill the Semantic Gap in Video Retrieval? A Case Study With Broadcast News
IEEE Transactions on Multimedia
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Concept detectors: how good is good enough?
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Beyond shot retrieval: searching for broadcast news items using language models of concepts
ECIR'2010 Proceedings of the 32nd European conference on Advances in Information Retrieval
Multimodal indexing based on semantic cohesion for image retrieval
Information Retrieval
Simulating the future of concept-based video retrieval under improved detector performance
Multimedia Tools and Applications
The uncertain representation ranking framework for concept-based video retrieval
Information Retrieval
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Describing shots through the occurrence of semantic concepts is the first step towards modeling the content of a video semantically. An important challenge is to automatically select the right concepts for a given information need. For example, systems should be able to decide whether the concept "Outdoor" should be included into a search for "Street Basketball". In this paper we provide an innovative method to automatically select concepts for an information need. To achieve this, we provide an estimation for the occurrence probability of a concept in relevant shots, which helps us to quantify the helpfulness of a concept. Our method reuses existing training data which is annotated with concept occurrences to build a text collection. Searching in this collection with a text retrieval system and knowing about the concept occurrences allows us to come up with a good estimate for this probability. We evaluate our method against a concept selection benchmark and search runs on both the TRECVID 2005 and 2007 collections. These experiments show that the estimation consistently improves retrieval effectiveness.