The vocabulary problem in human-system communication
Communications of the ACM
WordNet: a lexical database for English
Communications of the ACM
Experiments on using semantic distances between words in image caption retrieval
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
A cooccurrence-based thesaurus and two applications to information retrieval
Information Processing and Management: an International Journal
A language modeling approach to information retrieval
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Information retrieval as statistical translation
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Unifying textual and visual cues for content-based image retrieval on the World Wide Web
Computer Vision and Image Understanding - Special issue on content-based access for image and video libraries
Retrieval from captioned image databases using natural language processing
Proceedings of the ninth international conference on Information and knowledge management
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic image annotation and retrieval using cross-media relevance models
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
The Journal of Machine Learning Research
A layered approach to NLP-based information retrieval
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
A study of smoothing methods for language models applied to information retrieval
ACM Transactions on Information Systems (TOIS)
Building simulated queries for known-item topics: an analysis using six european languages
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Journal of High Speed Networks - Broadband Multimedia Sensor Networks in Healthcare Applications
Query side evaluation: an empirical analysis of effectiveness and effort
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Easing erroneous translations in cross-language image retrieval using word associations
CLEF'05 Proceedings of the 6th international conference on Cross-Language Evalution Forum: accessing Multilingual Information Repositories
Multimodal indexing based on semantic cohesion for image retrieval
Information Retrieval
Automatic generation of funny cartoons diary for everyday mobile life
AI'06 Proceedings of the 19th Australian joint conference on Artificial Intelligence: advances in Artificial Intelligence
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Users' search needs are often represented by words and images are retrieved according to such textual queries. Annotation words assigned to the stored images are most useful to connect queries to the images. However, due to annotation cost, quite limited amount of annotation words are available in many cases. When annotations are not given at all, there needs to be some techniques that assign annotations automatically. When only a few annotation words are given to each image (lightly annotated), there need to be some enhancement techniques that best use the available annotations. We address the later problem by estimating word associations to fill in the lexical gap between queries and annotations. The model of word associations can be learned from the data. However, since images are only lightly annotated, their sparseness in computing word associations becomes crucial. To compensate the sparseness, we propose a novel data exploration technique in which image similarities contribute to the estimation of word associations on the assumption that similar images have similar semantic concepts. We experimentally show the potential benefit of our approach.