Results 171 to 180 of about 8,324 (219)

Improvement and Application of TF * IDF Algorithm

2011
The traditional TF-IDF probability model is a relatively simple formula. For a few words which are commonly used and not stop words in a paper,it is lack of better differentiate and is not suitable for many specific cases, such as news advertising service module, about extraction of key words of the article, according to the deficiencies and the demand
Ji-Rui Li, Yan-Fang Mao, Kai Yang
openaire   +1 more source

Clustering the topics using TF-IDF for model fusion

Proceedings of the 2nd PhD workshop on Information and knowledge management, 2008
Users tend to express their queries in various ways: sometimes they use more general terms, sometimes more specific terms. Information retrieval systems need to be able to accommodate this variety of user needs. Some retrieval models perform better when the queries are general, others perform better when the queries are more specific, and others when a
Muath Alzghool, Diana Zaiu Inkpen
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The Automatic option of inference rules for the fuzzy TF-IDF

2020 IEEE 2nd International Conference on Electronics, Control, Optimization and Computer Science (ICECOCS), 2020
For several NLP tasks, we use the Fuzzy Inference System (FIS) to develop a set of decisional systems. Still, the selection rules FIS process needs some modification to be more useful. In this paper, we use FIS to produce terms weight for electronic documents basing on the popular TF-IDF (term frequency-inverse term frequency) components.
Mariem Bounabi, Karim El Moutaouakil, Khalid Satori   +2 more
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An information-theoretic perspective of tf–idf measures

Information Processing & Management, 2003
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Chinese readability assessment using TF-IDF and SVM

2011 International Conference on Machine Learning and Cybernetics, 2011
This paper proposes a simple yet effective method to automatically determine the readability of Chinese articles. We use mutual information to select the most important terms from the training data, calculate TF-IDF values based on those terms, and use those values as features for SVM to build classification models that identify articles suitable for ...
Yaw-Huei Chen, Yi-Han Tsai, Yu-Ta Chen
openaire   +1 more source

Research on case reasoning method based on TF-IDF

International Journal of System Assurance Engineering and Management, 2021
With the continuous expansion of the application field of Case-Based Reasoning (CBR) technology, it is increasingly difficult for programmers to acquire and express professional knowledge. Therefore, this paper first gives a structured expression of professional knowledge, and combines the Case-Based Reasoning method with the scientific measurement of ...
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Movie genre classification using TF-IDF and SVM

Proceedings of the 2019 7th International Conference on Information Technology: IoT and Smart City, 2019
This paper studies the classification principle and process of SVM algorithm, and classifies the text containing movie information, so as to achieve the research purpose of movie classification. It focuses on the various steps that need to be completed in the process of classification, such as text word segmentation, feature engineering, text ...
Ning Fei, Yangyang Zhang
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From Tf-Idf to Learning-to-Rank

2016
Ranking a set of documents based on their relevances with respect to a given query is a central problem of information retrieval (IR). Traditionally people have been using unsupervised scoring methods like tf-idf, BM25, Language Model etc., but recently supervised machine learning framework is being used successfully to learn a ranking function, which ...
Muhammad Ibrahim, Manzur Murshed
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Improvement of TF-IDF Algorithm Based on Knowledge Graph

2018 IEEE 16th International Conference on Software Engineering Research, Management and Applications (SERA), 2018
The TF-IDF algorithm is commonly used for text information retrieval and data mining. The traditional TF-IDF algorithm does not consider the domain characteristics of the article, and does not consider the distribution ratio. Currently, the solution proposed by many scholars only solves the problems of distribution ratio and the like, and does not ...
Yanpeng Wang, Dehai Zhang, Ye Yuan, Qing Liu 0019, Yun Yang 0003   +4 more
openaire   +1 more source

Ontology-Based Genes Similarity Calculation with TF-IDF

2012
The Gene Ontology (GO) provides a controlled vocabulary of terms for describing genes from different data resources. In this paper, we proposed a novel method determining semantic similarity of genes based on GO. The key principle of our method relies on the introduction of Term Frequency (TF) and Inverse Document Frequency (IDF) to quantify the ...
Yue Huang, Mingxin Gan, Rui Jiang 0001
openaire   +1 more source