Word sense disambiguation in information retrieval revisited
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
ConceptNet — A Practical Commonsense Reasoning Tool-Kit
BT Technology Journal
A cross-language document retrieval system based on semantic annotation
EACL '03 Proceedings of the tenth conference on European chapter of the Association for Computational Linguistics - Volume 2
Semantic similarity methods in wordNet and their application to information retrieval on the web
Proceedings of the 7th annual ACM international workshop on Web information and data management
Semantic knowledge extraction and annotation for web images
Proceedings of the 13th annual ACM international conference on Multimedia
Information retrieval with commonsense knowledge
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Web image indexing by using associated texts
Knowledge and Information Systems
Eliciting concepts of place for text-based image retrieval
Proceedings of the 4th ACM workshop on Geographical information retrieval
Query expansion with conceptnet and wordnet: an intrinsic comparison
AIRS'06 Proceedings of the Third Asia conference on Information Retrieval Technology
Web query expansion by wordnet
DEXA'05 Proceedings of the 16th international conference on Database and Expert Systems Applications
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Digital objects such as images and videos are fundamental resources in digital library. To assist in retrieving such objects usually they are being tagged by some keywords or sentences. The popular approach to tag digital objects is based on associated text. However, relying on associated text alone such as the surrounding text unable to semantically describe such objects. This paper discusses the use of WordNet and ConceptNet to tag digital images beyond terms available in the surrounding text. WordNet is used to disambiguate concepts or terms from the associated text and ConceptNet is meant to infer topics or common-sense knowledge from summarizing the text that describe the images. However, relying on WordNet alone is not sufficed particularly when it comes to disambiguate specific or domain dependent concepts. As such the Name Entity Recognition (NER) technique is required to annotate important entities such as name of a person, location and organization. Our work focused on on-lines news images that are richly described with textual description.