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IJSTR >> Volume 9 - Issue 3, March 2020 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Finding Similar Content Posts Using Semantic Textual Similarity Based On Text Segmentation Through Natural Language Processing

[Full Text]

 

AUTHOR(S)

Rohan C. Tadvi, Vrushali A. Chakkarwar

 

KEYWORDS

congruence, relatedness, clustering, classification, semantic, corpuses, forum, preprocessing.

 

ABSTRACT

Posts in the forums are dispersed in database where determining the congruence among the text posts in web forums is cumbersome task. Congruence is relevant property while text clustering and text classification. Traditionally the documents were searched with the collation of keywords or set of terms from the posts. Proposed system posts are contemplated as corpus of words where each entity in corpus has some individual weightage where terms and words are also found in another corpuses as well. To fulfill the objective with common goal there should be some relatedness among the corpus of different posts in different or same forum which provides the similar motive the user needed to deliver. Congruence is calculated by applying a score to common terms calculated in preprocessing. Semantic relatedness score of corpus differs for every corpus depending on the relatedness in corpuses. Posts are divided into segments at particular instances. Of these segments the corpuses are created and text features are extracted and monitored by identifying congruence of keywords. The common terms extracted are evaluated using process by combination of different Semantic Textual algorithms. After calculating the similarity most identical posts are displayed to user on threshold basis.

 

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