A multidimensional approach to blog mining

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dc.contributor.authorSandeep, K.S.
dc.contributor.authorPatil, N.
dc.date.accessioned2026-02-06T06:38:28Z
dc.date.issued2018
dc.description.abstractBlogs are textual web documents published by bloggers to share their experience or opinion about a particular topic(s). These blogs are frequently retrieved by the readers who are in need of such information. Existing techniques for text mining and web document mining can be applied to blogs to ease the blog retrieval. But these existing techniques consider only the content of the blogs or tags associated with them for mining topics from these blogs. This paper proposes a Multidimensional Approach to Blog Mining which defines a method to combine the Blog Content and Blog Tags to obtain Blog Patterns. These Blog Patterns represent a blog better when compared to Blog Content Patterns or Blog Tag Patterns. These Blog Patterns can either be used for Blog Clustering or used by Blog Retrieval Engines to compare with user queries. The proposed approach has been implemented and evaluated on real-world blog data. © Springer Nature Singapore Pte Ltd. 2018.
dc.identifier.citationAdvances in Intelligent Systems and Computing, 2018, Vol.519, , p. 51-58
dc.identifier.issn21945357
dc.identifier.urihttps://doi.org/10.1007/978-981-10-3376-6_6
dc.identifier.urihttps://idr.nitk.ac.in/handle/123456789/31701
dc.publisherSpringer Verlag service@springer.de
dc.subjectBlog clustering
dc.subjectBlog mining
dc.subjectBlogs
dc.subjectTags
dc.titleA multidimensional approach to blog mining

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