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Automatic Class Labeling for CiteSeerX

Surya Dhairya Kashireddy, Susan Gauch, Syed Masum Billah
2013 2013 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT)  
We evaluate three methods by comparing the suggested labels with human-assigned labels for exist-ing categories.  ...  To address this problem, we are exploring ways to automatically expand the CCS ontology. Previous work has focused on using clustering to automatically identify the new clas-ses.  ...  Our contributions are as follows: (1) we describe an automatic ontology expansion technique based on clustering; and (2) we evaluate a new labeling algorithm to label the newly created subclasses.  ... 
doi:10.1109/wi-iat.2013.35 dblp:conf/webi/KashireddyGB13 fatcat:7kb4ypr33je2fhqboeitrju3z4

Performance Evaluation of Manhattan and Euclidean Distance Measures For Clustering Based Automatic Text Summarization

Shakirat A Salihu, Ifeoma P Onyekwere, Modinat A Mabayoje, Hammed A Mojeed
2019 FUOYE Journal of Engineering and Technology  
In this paper, automatic text summarization with K-means clustering techniques is presented by employing two different distance measurement methods (Euclidean and Manhattan).  ...  The preprocessed document is converted into vector representation using tf-idf technique and k-means clustering is applied using Euclidean and Manhattan distance measures to generate summary.  ...  The future work can consider automatic determination of number of clusters to enhance K-means performance. Also, other distance measures can be considered for comprehensive evaluation.  ... 
doi:10.46792/fuoyejet.v4i1.316 fatcat:fpg32j6vqvdetim7phgy4vkd2e

Page 62 of SRELS Journal of Information Management Vol. 21, Issue 1 [page]

1984 SRELS Journal of Information Management  
But, more work needs to be done to establish theoretical basis for the use of automatic classification techniques as also for the construction of automatic classification schemes.  ...  The results of early experiments have been rather hard to interpret and evaluate. At present, there is a realization that automatic classification is desirable in principle.  ... 

Document clustering for electronic meetings: an experimental comparison of two techniques

Dmitri G Roussinov, Hsinchun Chen
1999 Decision Support Systems  
We have also measured the time that it takes for an expert to "clean up" the automatically produced clusters. The technique based on Ward's clustering was found to be more precise.  ...  We have evaluated how closely clusters produced by a computer resemble those created by human experts.  ...  Automatic indexing. 2. Selecting most discriminating terms. 3. Applying clustering technique: SOM or Ward's.  ... 
doi:10.1016/s0167-9236(99)00037-8 fatcat:rrk7q4miwraxlaebtco2uknvlq

Automatic Detection of Terminology Evolution [chapter]

Nina Tahmasebi
2009 Lecture Notes in Computer Science  
In this Ph.D. thesis we focus on automatically detecting terminology evolution in a completely unsupervised manner as described in this technical paper.  ...  As archives contain documents that span over a long period of time, the language used to create these documents and the language used for querying the archive can differ.  ...  Acknowledgements We would like to thank Times Newspapers Limited for providing the archive of The Times for our research.  ... 
doi:10.1007/978-3-642-05290-3_93 fatcat:vdn4r7oagjfpbnsdh7d3sujjlq

An Automatic Query Generation Approach for Arabic Corpus

Mohammed J.Bawaneh
2014 International Journal of Computer Applications  
This paper proposes an automatic query generation (AQG) system for Arabic language. The system generates a set of queries of different length that were applied on a query expansion system.  ...  Usually data sets of queries for a specific corpus are generated using the human experiences. Manual queries are more accurate than automatic one's, but they require a huge effort in the huge corpus.  ...  A lot of methods and techniques have been built to construct queries manually, but only few methods exist for automatically query construction.  ... 
doi:10.5120/18242-9340 fatcat:l6or2pbvejblfoaqynztd76uqa

Abstracting of legal cases

Marie-Francine Moens, Caroline Uyttendaele, Jos Dumortier
1997 Proceedings of the sixth international conference on Artificial intelligence and law - ICAIL '97  
The application of cluster algorithms based on the selection of representative objects has a potential for automatic theme recognition, text abstracting and text linking, even beyond the legal field.  ...  Techniques are developed for identifying and extracting relevant information from the cases. A broader application of these techniques could considerably simplify the work of the legal profession.  ...  Acknowledgements We thank Tine Bouwen for the verification of the results. We are grateful to Prof. Dr. L. Verstraelen, Dr. J. Leysen and Prof. Dr. J. Zeleznikow for helpful comments.  ... 
doi:10.1145/261618.261643 dblp:conf/icail/MoensUD97 fatcat:66l2bp355bdcrotyoabtbgl7tu

Ensemble-driven support vector clustering: From ensemble learning to automatic parameter estimation [article]

Dong Huang, Chang-Dong Wang, Jian-Huang Lai, Yun Liang, Shan Bian, Yu Chen
2016 arXiv   pre-print
In this paper, we propose a novel support vector clustering approach termed ensemble-driven support vector clustering (EDSVC), which for the first time tackles the automatic parameter estimation problem  ...  Support vector clustering (SVC) is a versatile clustering technique that is able to identify clusters of arbitrary shapes by exploiting the kernel trick.  ...  of unsupervised parameter estimation for SVC based on the ensemble clustering technique.  ... 
arXiv:1608.01198v2 fatcat:c4zytmagrjfrfhxfxb5xwcbcdi

A Self-enriching Methodology for Clustering Narrow Domain Short Texts

D. Pinto, P. Rosso, H. Jimenez-Salazar
2010 Computer journal  
We also propose a set of supervised and unsupervised text assessment measures for evaluating different corpus features, such as shortness, stylometry and domain broadness.  ...  The aim of this paper is to introduce a selfterm expansion methodology for improving the performance of clustering methods when dealing with corpora of this kind.  ...  ACKNOWLEDGEMENTS We thank the reviewers for their many helpful comments and suggestions.  ... 
doi:10.1093/comjnl/bxq069 fatcat:46hcjyggxbdqtjc5wyxo3ari2u

Automatic Document Classification
English

Babita Jaiswal
1999 DESIDOC Bulletin of Information Technology  
Automatic keyword classification is only an attempt. The use of automatically constructed classification is still a subject for investigation.  ...  Automatic classification is concertted with the procedures and systems that can make comparison between terms used.  ...  From its inception, the system was designed both as a retrieval tool and as a vehicle for evaluating the effectiveness of automatic search and analysis technique.  ... 
doi:10.14429/dbit.19.3.3486 fatcat:meeilbu36vc2robdlqu2ekq5kq

Toward (semi-)automatic generation of bio-medical ontologies

Vipul Kashyap, Cartic Ramakrishnan, Thomas C Rindflesch
2003 AMIA Annual Symposium Proceedings  
In the biomedical domain, we seek to leverage resources such as the UMLS Metathesaurus and NLP-based applications such as MetaMap in conjunction with statistical clustering techniques, to (partially) automate  ...  The design and construction of domain specific ontologies and taxonomies requires allocation of huge resources in terms of cost and time.  ...  Statistical techniques are suitable for unsupervised content-based clustering of documents.  ... 
pmid:14728391 pmcid:PMC1480321 fatcat:qqbwdvf33zeyjbzwe3a5whudyi

Automatic clustering of bug reports

Maen Hammad, Ruba Alzyoudi, Ahmed Fawzi Otoom
2018 International Journal of Advanced Computer Research  
A set of terms is extracted from each cluster, as tags, to help maintainers to understand the issue, topic or feature handled by the bug reports in the cluster.  ...  An experimental study is applied and discussed, followed by manual evaluation of the bug reports in the generated clusters.  ...  It combines text clustering, frequent term calculations and taxonomic term mapping techniques. The algorithm CLUBAS is an example of classification using clustering techniques. In Nagwani et al.  ... 
doi:10.19101/ijacr.2018.839013 fatcat:5idduf6iljgrljdus4ll44v5su

Automatic labeling of software requirements clusters

Nan Niu, Sandeep Reddivari, Anas Mahmoud, Tanmay Bhowmik, Songhua Xu
2012 2012 4th International Workshop on Search-Driven Development: Users, Infrastructure, Tools, and Evaluation (SUITE)  
Despite the development of automated cluster labeling techniques in information retrieval, little is understood about automatic labeling of requirements clusters.  ...  In this paper, we review the literature on cluster labeling, and conduct an experiment to evaluate how automated methods perform in labeling requirements clusters.  ...  ACKNOWLEDGEMENT Songhua Xu performed this research as a Eugene P. Wigner Fellow and staff member at the Oak Ridge National Laboratory, managed by UT-Battle, LLC, for the U.S.  ... 
doi:10.1109/suite.2012.6225472 fatcat:o5l73n5xuzft3f665hbzokkgna

Automatic Construction of Lightweight Domain Ontologies for Chemical Engineering Risk Management [article]

Wilson Wong, Wei Liu, Saujoe Liaw, Nicoletta Balliu, Hongwei Wu, Moses Tade
2008 arXiv   pre-print
Initial experiments using a working prototype of the system revealed promising potentials in automatically constructing high-quality domain ontologies using real-world texts.  ...  Most research on ontology learning conducted in the academia remains unrealistic for real-world applications.  ...  The ability to identify and isolate outliers, and to produce consistent results makes T T A a reliable term clustering technique.  ... 
arXiv:0812.3478v1 fatcat:lonskqu25bdv5ardttptxhfoia

Color Image Segmentation Based on Different Color Space Models Using Automatic GrabCut

Dina Khattab, Hala Mousher Ebied, Ashraf Saad Hussein, Mohamed Fahmy Tolba
2014 The Scientific World Journal  
The automatic GrabCut utilizes the unsupervised Orchard and Bouman clustering technique for the initialization phase.  ...  This paper presents a comparative study using different color spaces to evaluate the performance of color image segmentation using the automatic GrabCut technique.  ...  The average error rate is 3.64% for the automatic GrabCut compared to 4.28% for the original GrabCut technique.  ... 
doi:10.1155/2014/126025 pmid:25254226 pmcid:PMC4165205 fatcat:ffv2yiitdnerxkcqnybgzktwwa
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