Efficient phrase-based document indexing for Web document clustering

By Khaled M. Hammouda, Mohamed S. Kamel. IEEE Transactions on Knowledge and Data Engineering, 2004

375 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems

View Paper: https://www.semanticscholar.org/paper/0027d580b2ab37a49358d4490021e1bef1af3af5

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Citations in the corpus

Personalized news recommendation using classified keywords to capture user preference (2014, methodology): “News categorization is studied using document clustering [5] and document indexing [6].”
Detecting near-duplicates for web crawling (2007, methodology): “The idea of using phrases also appears in the work of Hammouda and Kamel [32] who build sophisticated indexing techniques for web-clustering.”
Data Mining for Internet of Things: A Survey (2014, methodology): “These methods can be found in some previous data mining studies, such as random sampling [28], data condensation [29], divide and conquer [30], and incremental learning [31].”
Fundamentals of Information Studies: Understanding Information and Its Environment, Second Edition (2009, methodology): “The phrase matching approach has been applied successfully in detecting similar documents [9, 19]; however, these previous works focus on exact phrase matching, instead of (inexact) similar phrase matching, which is more sophisticated and its accuracy has been verified by us with a 96% accuracy rate”
A new suffix tree similarity measure for document clustering (2007, methodology): “Any clustering technique replies on four concepts: data representation model, similarity measure, clustering model and clustering algorithm that generates the clusters using the data model and the similarity measure [7].”
A new sentence similarity measure and sentence based extractive technique for automatic text summarization (2009, background): “Various methods/criteria have been proposed over the years from various perspectives and with various focuses (Hammouda & Kamel, 2004).”
A Similarity Measure for Text Classification and Clustering (2014, background): “Such highdimensionality and sparsity can be a severe challenge for similarity measure which is an important operation in text processing algorithms [5], [6], [10], [11], [23], [24], [28], [30], [33], [34], [37], [41], [42], [47], [49], [50].”