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Term Weighting Using Term Dependence
International Journal of Computer Applications, 2010 Performance of an information retrieval system depends on its weighting scheme. Weighting of a term can be seen in two aspects, local and global. For each type of weighting scheme, generally, single terms are considered. Term dependency is quite natural in a document. Word pairs or phrases can better describe a document in place of single terms. In the
Raj Kishor Bisht +2 more
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Investigating sentence weighting components for automatic summarisation [PDF]
, 2006 The work described here initially formed part of a triangulation exercise to establish the effectiveness of the Query Term Order algorithm. The methodology produced subsequently proved to be a reliable indicator of quality for summarising English web ...
Bates +16 more
core +1 more source
Cluster Based Term Weighting Model for Web Document Clustering [PDF]
, 2014 The term weight is based on the frequency with which the term appears in that document. The term weighting scheme measures the importance of a term with respect to a document and a collection.
Amit Singhal +8 more
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A New Term Frequency with Gaussian Technique for Text Classification and Sentiment Analysis
Journal of ICT Research and Applications, 2021 This paper proposes a new term frequency with a Gaussian technique (TF-G) to classify the risk of suicide from Thai clinical notes and to perform sentiment analysis based on Thai customer reviews and English tweets of travelers that use US airline ...
Vuttichai Vichianchai +1 more
doaj +1 more source
Combining and selecting characteristics of information use [PDF]
, 2002 In this paper we report on a series of experiments designed to investigate the combination of term and document weighting functions in Information Retrieval.
Lalmas, M. +2 more
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Generating Term Weighting Schemes Through Genetic Programming [PDF]
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2018 Term-Weighting Scheme (TWS) is an important step in text classification. It determines how documents are represented in the Vector Space Model (VSM). Even though state-of-the-art TWSs exhibit good behaviors, a large number of new works propose new approaches and new TWSs that improve performances. Furthermore, it is still difficult to tell which TWS is
Mazyad, Ahmad +2 more
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Credibility Adjusted Term Frequency: A Supervised Term Weighting Scheme for Sentiment Analysis and Text Classification [PDF]
, 2014 We provide a simple but novel supervised weighting scheme for adjusting term frequency in tf-idf for sentiment analysis and text classification. We compare our method to baseline weighting schemes and find that it outperforms them on multiple benchmarks.
Kim, Yoon, Zhang, Owen
core +1 more source
Categorization of Unorganized Text Corpora for better Domain-Specific Language Modeling
Advances in Electrical and Electronic Engineering, 2013 This paper describes the process of categorization of unorganized text data gathered from the Internet to the in-domain and out-of-domain data for better domain-specific language modeling and speech recognition.
Jan Stas +3 more
doaj +1 more source
Optimizing Document Retrieval by Measurement Resemblance Between Semantic Word Methods
วารสารวิทยาการสารสนเทศและเทคโนโลยีประยุกต์, 2020 The aims of article to present the method for measuring semantic similarity between words. Data test are documents in the computer domain from ThaiLIS : Thai Library Integration System 50 documents and prepare a Dublin Core metadata for documentation ...
Kamonwan Ratchatawetchakul +3 more
doaj +1 more source
International Journal of Information Management Data Insights, 2022 One of the challenging tasks in text classification is to reduce the dimensional feature space. This paper discusses an enhanced text classification method using Bag-of-Words representation model with term frequency-inverse document frequency (tf-idf ...
Ksh. Nareshkumar Singh +3 more
doaj +1 more source