scholarly journals Deteksi Duplikasi Metadata File pada Media Penyimpanan menggunakan Metode Latent Semantic Analysis

2020 ◽  
Vol 5 (1) ◽  
pp. 119
Author(s):  
Erlin Erlin ◽  
Boby Hasbul Fikri ◽  
Susanti Susanti ◽  
Triyani Arita Fitri
Keyword(s):  
Data Storage ◽  
Latent Semantic Analysis ◽  
Semantic Analysis ◽  
Relevant Information ◽  
Analysis Method ◽  
Storage Media ◽  
Digital Identification ◽  
Metadata File ◽  
Media Space ◽  
Data Files

Metadata files help user find relevant information, provides digital identification, archives and conserves stored files so that they are easily found and reused. The large number of data files on the storage media often makes the user unaware of the duplication and redundancy of the files that have an impact on the waste of storage media space, affecting the speed of a computer in the indexing process, finding or backing up data. This study employ the Latent Semantic Analysis method to detect file duplication and analyze the metadata of various file types in storage media. The findings showed that Latent Semantic Analysis method is able to detect duplicate file metadata in various types of storage media thereby further increasing the usability and speed of access of the data storage media.

scholarly journals Finding author similarity by clustering probabilistic LSA factors in INDIAN english authors poetry

2018 ◽  
Vol 7 (2.7) ◽  
pp. 1096
Author(s):  
K Praveen kumar ◽  
Venkata Naresh Mandhala ◽  
Sudheshna Vempati ◽  
Dr Subba Rao Peram
Keyword(s):  
Latent Semantic Analysis ◽  
Semantic Analysis ◽  
Probabilistic Methods ◽  
Distance Measures ◽  
High Dimensionality ◽  
Probabilistic Latent Semantic Analysis ◽  
Analysis Method ◽  
Indian English ◽  
Clear Distance ◽  
Learning Data

High dimensionality and sparseness is the big challenge to the data scientists to discover the similarity among the documents. In unsuper-vised learning data is unlabeled and there is no clear distance measures to discover the clusters among the data. In this paper we considered Indian English Authors poems to cluster them using Probabilistic Latent Semantic Analysis, using which we analyzed the authors similarity. We compared the results of clustering with Latent Semantic Analysis method, a word occurrence method. In this case, Results are shown that probabilistic methods are performing good clustering than the word occurrence method.  

scholarly journals Otomatisasi Peringkasan Teks Pada Dokumen Hukum Menggunakan Metode Latent Semantic Analysis

2021 ◽  
Vol 7 (3) ◽  
pp. 9-16
Author(s):  
Millenia Rusbandi ◽  
Imam Fahrur Rozi ◽  
Kadek Suarjuna Batubulan
Keyword(s):  
Law Enforcement ◽  
Latent Semantic Analysis ◽  
Semantic Analysis ◽  
Compression Rate ◽  
Analysis Method ◽  
Legal Documents ◽  
Automatic Text Summarization ◽  
Long Time ◽  
Law Enforcement Officials ◽  
Automatic Text

At present, the number of crimes in Indonesia is quite large. The large number of crimes in Indonesia will have an impact on the number of legal documents that will be handled by law enforcement officials. In understanding legal documents, law enforcement officials such as lawyers, judges, and prosecutors must read the entire document which will take a long time. Therefore a summary is needed so that law enforcement officials can understand it more easily. So that one solution needed is to make a summary of the legal documents where the documents are in PDF form. In terms of summarizing the text, the method that can be used is the Latent Semantic Analysis algorithm. The algorithm is used to describe or analyze the hidden meaning of a language, code or other type of representation in order to obtain important information.From testing the 10 documents summarized by experts, the results of precision, recall, f-measure and accuracy are obtained sequentially on automatic text summarization using the Latent Semantic Analysis method for a compression rate of 75%, namely 53%, 27%, 35% and 71%. for a compression rate of 50%, namely 54%, 56%, 55% and 75%, and for a compression rate of 25%, namely 51%, 79%, 61% and 75%. Based on the results of the research and testing that has been done, it can be concluded that the Latent Semantic Analysis Method can be used to summarize legal documents.

Issues and Methods for Access, Storage, and Analysis of Data From Online Social Communities

2018 ◽  
pp. 402-432
Author(s):  
Christopher John Quinn ◽  
Matthew James Quinn ◽  
Alan Olinsky ◽  
John Thomas Quinn
Keyword(s):  
Social Network ◽  
Data Storage ◽  
Latent Semantic Analysis ◽  
Information Diffusion ◽  
Latent Dirichlet Allocation ◽  
Semantic Analysis ◽  
Online Social Network ◽  
Network Models ◽  
Probabilistic Latent Semantic Analysis ◽  
User Interactions

This chapter provides an overview for a number of important issues related to studying user interactions in an online social network. The approach of social network analysis is detailed along with important basic concepts for network models. The different ways of indicating influence within a network are provided by describing various measures such as degree centrality, betweenness centrality and closeness centrality. Network structure as represented by cliques and components with measures of connectedness defined by clustering and reciprocity are also included. With the large volume of data associated with social networks, the significance of data storage and sampling are discussed. Since verbal communication is significant within networks, textual analysis is reviewed with respect to classification techniques such as sentiment analysis and with respect to topic modeling specifically latent semantic analysis, probabilistic latent semantic analysis, latent Dirichlet allocation and alternatives. Another important area that is provided in detail is information diffusion.

scholarly journals Perbandingan Hasil Deteksi Plagiarisme Dokumen dengan Metode Jaro-Winkler Distance dan Metode Latent Semantic Analysis

2018 ◽  
Vol 6 (1) ◽  
pp. 7-12 ◽  
Author(s):  
Tinaliah Tinaliah ◽  
Triana Elizabeth
Keyword(s):  
Test Data ◽  
Latent Semantic Analysis ◽  
Semantic Analysis ◽  
Analysis Method ◽  
Plagiarism Detection ◽  
Distance Method ◽  
Better Than

Various methods are applied in the application of plagiarism detection to help check the similarity of a document. Jaro-Winkler Distance can measure the distance between two strings. However, this method basically depends on the position of the word. Latent Semantic Analysis emphasizes the words contained in the document regardless of its linguistic character. This study compares the results of plagiarism detection using the Jaro-Winkler Distance and the Latent Semantic Analysis method. From comparing results of  Jaro-Winkler Distance method and Latent Semantic Analysis method, Jaro-Winkler Distance method is better than Latent Semantic Analysis method if using the same test data. Jaro-Winkler Distance method will give plagiarism result 100% and Latent Semantic Analysis method will give plagiarism result 97,14%.

scholarly journals Biomedical Literature Exploration through Latent Semantics

2013 ◽  
Vol 2 (2) ◽  
pp. 65-74 ◽  
Author(s):  
Sérgio Matos ◽  
Hugo Araújo ◽  
José Luís Oliveira
Keyword(s):  
Latent Semantic Analysis ◽  
Literature Search ◽  
Semantic Information ◽  
Semantic Analysis ◽  
Biomedical Literature ◽  
Analysis Method ◽  
Biomedical Field ◽  
Visualization Techniques ◽  
Knowledge Exploration ◽  
The Way

The fast increasing amount of articles published in the biomedical field is creating difficulties in the way this wealth of information can be efficiently exploited by researchers. As a way of overcoming these limitations and potentiating a more efficient use of the literature, we propose an approach for structuring the results of a literature search based on the latent semantic information extracted from a corpus. Moreover, we show how the results of the Latent Semantic Analysis method can be adapted so as to evidence differences between results of different searches. We also propose different visualization techniques that can be applied to explore these results. Used in combination, these techniques could empower users with tools for literature guided knowledge exploration and discovery.

Task Estimation Using Latent Semantic Analysis of Visual Scenes and Spoken Words

2012 ◽  
Vol 132 (9) ◽  
pp. 1473-1480
Author(s):  
Masashi Kimura ◽  
Shinta Sawada ◽  
Yurie Iribe ◽  
Kouichi Katsurada ◽  
Tsuneo Nitta
Keyword(s):  
Latent Semantic Analysis ◽  
Semantic Analysis ◽  
Spoken Words ◽  
Visual Scenes
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