A Hybrid Information Retrieval for Indonesian Translation of Quran by Using Single Pass Clustering Algorithm

The World Wide Web is a large distributed digital information space. The ability to search and retrieve information from the Web efficiently and effectively is an enabling technology for realizing its full potential. Information Retrieval (IR) plays an important role in search engines. Today’s most advanced engines use the keyword-based (“bag of words”) paradigm, which has inherent disadvantages. Organizing web search results into clusters facilitates the user’s quick browsing of search results. Traditional clustering techniques are inadequate because they do not generate clusters with highly readable names. This paper proposes an approach for web search results in clustering based on a phrase based clustering algorithm. It is an alternative to a single ordered result of search engines. This approach presents a list of clusters to the user. Experimental results verify the method’s feasibility and effectiveness.

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Multispectral Analysis of IRAS Sky Flux Maps

Symposium - International Astronomical Union ◽

10.1017/s0074180900240679 ◽

1990 ◽

Vol 139 ◽

pp. 214-215

Author(s):

L. G. Balázs ◽

M. Kun ◽

V. Tóth

Keyword(s):

Principal Components Analysis ◽

Principal Components ◽

Clustering Algorithm ◽

Cosmic Dust ◽

Training Set ◽

Single Pass ◽

Components Analysis ◽

Multispectral Analysis ◽

Main Components

We have tested the performance of principal components analysis and a single-pass clustering algorithm to identify different components of the cosmic dust. Applying these techniques on a training set of 2500 points extracted from the PL51 IRAS maps we recognized two main components with temperatures of 180 K and 28 K.

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An Improved Clustering Algorithm based on Single-pass

Proceedings of the 2019 2nd International Conference on Data Science and Information Technology ◽

10.1145/3352411.3352442 ◽

2019 ◽

Author(s):

Biao Wang ◽

Xin Yuan ◽

Jinwei Li ◽

Shun Li

Keyword(s):

Clustering Algorithm ◽

Single Pass

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A clustering technique using single pass clustering algorithm for search engine

2014 4th World Congress on Information and Communication Technologies (WICT 2014) ◽

10.1109/wict.2014.7077325 ◽

2014 ◽

Cited By ~ 2

Author(s):

Zul Indra ◽

Norshuani Zamin ◽

Jafreezal Jaafar

Keyword(s):

Search Engine ◽

Clustering Algorithm ◽

Single Pass ◽

Clustering Technique

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Ontology based clustering algorithm for information retrieval

2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT) ◽

10.1109/icccnt.2013.6726605 ◽

2013 ◽

Author(s):

T. Nadana Ravishankar ◽

R. Shriram

Keyword(s):

Information Retrieval ◽

Clustering Algorithm

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A Roadmap to Integrate Document Clustering in Information Retrieval

International Journal of Information Retrieval Research ◽

10.4018/ijirr.2011010103 ◽

2011 ◽

Vol 1 (1) ◽

pp. 31-44 ◽

Cited By ~ 1

Author(s):

R. Subhashini ◽

V.Jawahar Senthil Kumar

Keyword(s):

Information Retrieval ◽

Search Engines ◽

Clustering Algorithm ◽

Web Search ◽

Full Potential ◽

Digital Information ◽

Enabling Technology ◽

Clustering Techniques ◽

Search Results ◽

The World

The World Wide Web is a large distributed digital information space. The ability to search and retrieve information from the Web efficiently and effectively is an enabling technology for realizing its full potential. Information Retrieval (IR) plays an important role in search engines. Today’s most advanced engines use the keyword-based (“bag of words”) paradigm, which has inherent disadvantages. Organizing web search results into clusters facilitates the user’s quick browsing of search results. Traditional clustering techniques are inadequate because they do not generate clusters with highly readable names. This paper proposes an approach for web search results in clustering based on a phrase based clustering algorithm. It is an alternative to a single ordered result of search engines. This approach presents a list of clusters to the user. Experimental results verify the method s feasibility and effectiveness.

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Enhanced Search Result Using Improved Clustering Algorithm for Information Retrieval

Journal of Convergence Information Technology ◽

10.4156/jcit.vol7.issue4.23 ◽

2012 ◽

Vol 7 (4) ◽

pp. 191-196

Author(s):

He Li ◽

Tang Jun

Keyword(s):

Information Retrieval ◽

Clustering Algorithm ◽

Search Result

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Modified Single Pass Clustering Algorithm Based on Median as a Threshold Similarity Value

Collaborative Filtering Using Data Mining and Analysis - Advances in Data Mining and Database Management ◽

10.4018/978-1-5225-0489-4.ch002 ◽

2017 ◽

pp. 24-48 ◽

Cited By ~ 1

Author(s):

Mamta Mittal ◽

R. K. Sharma ◽

V.P. Singh ◽

Lalit Mohan Goyal

Keyword(s):

Data Mining ◽

Clustering Algorithm ◽

Clustering Algorithms ◽

Data Mining Techniques ◽

Single Pass ◽

Hidden Patterns ◽

Data Objects

Clustering is one of the data mining techniques that investigates these data resources for hidden patterns. Many clustering algorithms are available in literature. This chapter emphasizes on partitioning based methods and is an attempt towards developing clustering algorithms that can efficiently detect clusters. In partitioning based methods, k-means and single pass clustering are popular clustering algorithms but they have several limitations. To overcome the limitations of these algorithms, a Modified Single Pass Clustering (MSPC) algorithm has been proposed in this work. It revolves around the proposition of a threshold similarity value. This is not a user defined parameter; instead, it is a function of data objects left to be clustered. In our experiments, this threshold similarity value is taken as median of the paired distance of all data objects left to be clustered. To assess the performance of MSPC algorithm, five experiments for k-means, SPC and MSPC algorithms have been carried out on artificial and real datasets.

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