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Rule-based word clustering for text classification

Hui Han, Eren Manavoglu, C. Lee Giles, Hongyuan Zha
2003 Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval - SIGIR '03  
This paper introduces a rule-based, context-dependent word clustering method, with the rules derived from various domain databases and the word text orthographic properties.  ...  Besides significant dimensionality reduction, our experiments show that such rule-based word clustering improves by 8% the overall accuracy of extracting bibliographic fields from references, and by 18.32%  ...  ACKNOWLEDGMENTS We acknowledge Andrew McCallum for providing the HMM code and Cheng Li for useful suggestions through the experiments.  ... 
doi:10.1145/860500.860543 fatcat:hkz7xpquwjbrbf74m3ypgjypje

Rule-based word clustering for text classification

Hui Han, Eren Manavoglu, C. Lee Giles, Hongyuan Zha
2003 Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval - SIGIR '03  
This paper introduces a rule-based, context-dependent word clustering method, with the rules derived from various domain databases and the word text orthographic properties.  ...  Besides significant dimensionality reduction, our experiments show that such rule-based word clustering improves by 8% the overall accuracy of extracting bibliographic fields from references, and by 18.32%  ...  ACKNOWLEDGMENTS We acknowledge Andrew McCallum for providing the HMM code and Cheng Li for useful suggestions through the experiments.  ... 
doi:10.1145/860435.860543 dblp:conf/sigir/HanMGZ03 fatcat:tmp5jkkrqvcxnfmaavszyadl2u

An Enhanced Association Rule Mining Method for Processing Network Comments

Yang Di, Wen Chengyu
2019 International Journal of Computer Applications Technology and Research  
These rules contain a large number of relational facts, which can reflect the relationship between plain text data, and can be effectively used in emotional classification of text.  ...  Firstly, NEARM clusters the original data containing the pairs of related entities into clusters with different granularity from the data in KBs, and then excavates the rules in each cluster.  ...  I would like to thank them for their help in helping me to complete this paper successfully.  ... 
doi:10.7753/ijcatr0807.1006 fatcat:xeysq3oxa5eqjguymfr5onu3mm

Rule-based word clustering for document metadata extraction

Hui Han, Eren Manavoglu, Hongyuan Zha, Kostas Tsioutsiouliklis, C. Lee Giles, Xiangmin Zhang
2005 Proceedings of the 2005 ACM symposium on Applied computing - SAC '05  
This paper introduces a domain Rule-based word clustering method for cluster feature representation. The clusters are formed from various domain databases and the word orthographic properties.  ...  Text classification is still an important problem for unlabeled text; CiteSeer, a computer science document search engine, uses automatic text classification methods for document indexing.  ...  Acknowledgments We gratefully acknowledge Andrew McCallum for providing the HMM code and Cheng Li for useful suggestions throughout the experiments.  ... 
doi:10.1145/1066677.1066917 dblp:conf/sac/HanMZTGZ05 fatcat:bd4uexds5zdxvofvac575fpwwy

Text Classification based on Association Rule Mining Technique

Meenakshi Mishra, Santosh K.
2017 International Journal of Computer Applications  
Finally, a comprehensive experimental study against FIRE data set is presented to evaluate and compare traditional and association rule based classification techniques with regards to classification performance  ...  The Paper also considers the use of association rule mining in classification approach in which a comparative study of Naïve Bayes Classifier and KNN is performed for this purpose.  ...  [4] , published an approach for text classification is proposed using association rule mining (ARM) with critical relative support (CRS) based pruning.  ... 
doi:10.5120/ijca2017914905 fatcat:nov3hn4chzheflshpe4wnua5jq

A Technical Study and Analysis on Fuzzy Similarity Based Models For Text Classification

Shalini Puri
2012 International Journal of Data Mining & Knowledge Management Process  
In this new and current era of technology, advancements and techniques, efficient and effective text document classification is becoming a challenging and highly required area to capably categorize text  ...  Such study and technical review provide a strong base of research work done on fuzzy similarity based text document categorization.  ...  Vikas Saxena, Dept. of Computer Science, Jaypee Institute of Information Technology, Noida, Uttar Pradesh, India for their help and guidance.  ... 
doi:10.5121/ijdkp.2012.2201 fatcat:fkka4kow6jg4jpd22bufgwhkqe

A survey on phrase structure learning methods for text classification [article]

Reshma Prasad, Mary Priya Sebastian
2014 arXiv   pre-print
Text classification is a task of automatic classification of text into one of the predefined categories.  ...  The performance of text classification improves notably when phrase patterns are used.  ...  There are different methods for text classification which includes decision trees [2] , rule based classifiers [5] , SVM classifiers [7] , neural network classifiers [4] , bayesian classifiers [3]  ... 
arXiv:1406.5598v1 fatcat:ekq6krnydrchjiovfqs6n2nuia

Use of Word Clustering to Improve Emotion Recognition from Short Text

Shuai Yuan, Huan Huang, Linjing Wu
2016 Journal of Computing Science and Engineering  
An effective approach to recognizing emotion from text is based on a machine learning technique, which deals with emotion recognition as a classification problem.  ...  This paper proposes to resolve the problem of feature sparseness, and largely improve the emotion recognition performance from short texts by doing the following: representing short texts with word cluster  ...  by the National Nature Science Foundation of China (No. 61272205), and supported by the Educational Science Planning in Hubei Province (No. 2015GB025), and supported by the Fundamental Research Funds for  ... 
doi:10.5626/jcse.2016.10.4.103 fatcat:7w3l2phjhrgadiuvhmwpyqxgae

Classification Recognition Algorithm Based on Strong Association Rule Optimization of Neural Network

Zhang Xuewu, Joern Huenteler
2016 TELKOMNIKA (Telecommunication Computing Electronics and Control)  
For this problem, a textual feature generating algorithm based on clustering weighting is adopted.  ...  Feature selection of text is one of the basic matters for intelligent classification of text. Textual feature generating algorithm adopts weighted textual vector space model generally at present.  ...  The text classification refers to automatic classification of text written in natural language based on the predefined subject style.  ... 
doi:10.12928/telkomnika.v14i2a.4364 fatcat:swzsldxrr5hyhl4pdzgplk6ffa

Survey on Research Paper Classification based on TF-IDF and Stemming Technique using Classification Algorithm

Kshitija G., S. A.
2020 International Journal of Computer Applications  
Text classification is a growing interest within the research of text mining. This paper presents a survey on classification algorithm and stemming technique used for Text classification.  ...  Text classification and class prediction is important for paper classification to reduce the feature size and to speed up the learning process of classifiers.  ...  K-means methodology to capture many cluster centroids for every class, and then select the high frequency words in centroids because the text features for categorization.  ... 
doi:10.5120/ijca2020920248 fatcat:6jitlc3dajczticyln6bvbszte

A Review on Knowledge Discovery using Text Classification Techniques in Text Mining

Chauhan ShrihariR, Amish Desai
2015 International Journal of Computer Applications  
The goal of the paper is to review and understand different text classification techniques and finding the best one out for different prospective.  ...  A text mining frame work contain preprocess on text and techniques used to retrieve information like classification, clustering, summarization, information extraction, and visualization. .  ...  ART system ignore the order of word its only focus on word. system based on TF-IDF And consist three phase 1) Pre processing. 2) Association rule mining algorithm for generate association rule based on  ... 
doi:10.5120/19542-0784 fatcat:xwgei3efuvbtzktmu45sdt73hy

ENHANCEMENT OF TEXT BASED EMOTION RECOGNITION PERFORMANCES USING WORD CLUSTERS

Adarsh S R
2019 International journal of research - granthaalayah  
along with word cluster features, (II) Presenting a narrative word clustering algorithm, and (iii) Making use of a new feature weighting scheme of the Emotion classification.  ...  The experimental results suggest that the text words cluster features and the proposed weighting scheme can moderately resolve the problems of the emotion recognition performance and the feature sparseness  ...  TN India, to improve the quality of the research techniques of AI applied in Text based HCI.  ... 
doi:10.29121/granthaalayah.v7.i1.2019.1051 fatcat:ylttkayqmzazvdvjtagukppb7y

Text Mining Using Metadata for Generation of Side Information

Shraddha S. Bhanuse, Shailesh D. Kamble, Sandeep M. Kakde
2016 Procedia Computer Science  
To achieve this, there is scope of improvement in generating side information i.e. selecting efficient classification and clustering algorithms, providing security for clustered side information, document  ...  In many metadata based text mining applications, side information also known as metadata which is associated with the text document.  ...  For classification rules are used. SVM Classifiers are used for partition the data space 30 . Neural Network Classifier 23 is used for text classification 16 .  ... 
doi:10.1016/j.procs.2016.02.061 fatcat:7rjgaacqkneetdbmfktpi2o6wa

POLICE USE OF SOCIAL MEDIA: COMPARING CLASSIFICATION METHODS

2019 Issues in Information Systems  
Domain expertise is often needed to classify text effectively, but it is unlikely to be found in the tools that provide the means for unsupervised classification.  ...  This paper examines a variety of text classification techniques applied to the domain of policing in the U.S.  ...  The text rule builder uses the words found in the tweets, along with the predefined category, to build rules for making classification decisions.  ... 
doi:10.48009/3_iis_2019_175-185 fatcat:spaq7psbr5dsplcfcgucyvmkmu

Method of Feature Reduction in Short Text Classification Based on Feature Clustering

Li, Yin, Shi, Mao, Shi
2019 Applied Sciences  
Here, a feature reduction method is proposed that is based on two-stage feature clustering (TSFC), which is applied to short text classification.  ...  Next, intra-cluster feature screening rules are designed to remove outlier feature words, which improves the effect of similar feature clusters.  ...  , which are utilized to replace the original feature vectors for short text classification.  ... 
doi:10.3390/app9081578 fatcat:o7qnx7svozb6vdh3zeq326ikya
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