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Word Classification and Hierarchy Using Co-Occurrence Word Information
Information Processing and Management, 2004zbMATH Open Web Interface contents unavailable due to conflicting licenses.
El-Sayed Atlam +2 more
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Using the Co-occurrence of Words for Retrieval Weighting
Information Retrieval, 2000Summary: We have applied the well-known Robertson-Sparck Jones weighting to sets of indexing features that are different from word-based features. Our features describe the co-occurrences of words in a window range of predefined size. The experiments have been designed to analyse the value of features that are beyond word-based features but all used ...
Elke Mittendorf +2 more
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Keyword Extraction Using Word Co-Occurrence
2010 Workshops on Database and Expert Systems Applications, 2010A common strategy to assign keywords to documents is to select the most appropriate words from the document text. One of the most important criteria for a word to be selected as keyword is its relevance for the text. The tf.idf score of a term is a widely used relevance measure.
Christian Wartena, Wout Slakhorst
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Word discrimination based on bigram co-occurrences
Proceedings of Sixth International Conference on Document Analysis and Recognition, 2002Very few pairs of English words share exactly the same letter bigrams. This linguistic property can be exploited to bring lexical context into the classification stage of a word recognition system. The lexical n-gram matches between every word in a lexicon and a subset of reference words can be precomputed.
Adnan El-Nasan +2 more
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Word co-occurrence features for text classification
Information Systems, 2011In this article we propose a data treatment strategy to generate new discriminative features, called compound-features (or c-features), for the sake of text classification. These c-features are composed by terms that co-occur in documents without any restrictions on order or distance between terms within a document.
Fábio Figueiredo +5 more
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Image estimation of words based on adjective co‐occurrences
Systems and Computers in Japan, 2007AbstractIn natural language, words convey various impressions such as “kurai (dark)‐akarui (bright)” or “kitanai (dirty)‐utsukushii (beautiful).” Impressions play an important role in inferring the speaker's intentions or feelings. Systems that use natural language to support conceptualization or retrieve information by teaching the computer the ...
Kouhei Shimizu, Masafumi Hagiwara
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Exploiting visual word co-occurrence for image retrieval
Proceedings of the 20th ACM international conference on Multimedia, 2012Bag-of-visual-words (BOVW) based image representation has received intense attention in recent years and has improved content based image retrieval (CBIR) significantly. BOVW does not consider the spatial correlation between visual words in natural images and thus biases the generated visual words towards noise when the corresponding visual features ...
Miaojing Shi +3 more
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