@prefix sioc: <http://rdfs.org/sioc/ns#> .
@prefix sioct: <http://rdfs.org/sioc/types#> .
@prefix dc: <http://purl.org/dc/elements/1.1/> .
@prefix dcterms: <http://purl.org/dc/terms/> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .
@prefix content: <http://purl.org/rss/1.0/modules/content/> .
@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .
@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .

<http://lib.itenas.ac.id/kti/?p=4238>
  a sioc:Post, sioct:BlogPost ;
  dc:title "IMPLEMENTASI MAXIMUM MARGINAL RELEVANCE DAN MATRIKS COSINE SIMILARITY PADA APLIKASI PERINGKASAN DOKUMEN" ;
  dcterms:identifier 4238 ;
  dc:modified "2015-03-30"^^xsd:date ;
  dc:created "2015-03-30"^^xsd:date ;
  sioc:link <http://lib.itenas.ac.id/kti/?p=4238> ;
  sioc:has_creator <http://lib.itenas.ac.id/kti/?author=6#account> ;
  sioc:has_container <http://lib.itenas.ac.id/kti/#posts> ;
  dc:abstract "" ;
  content:encoded """<![CDATA[Automatic Text Summarization are sorting paragraphs into shorter forms using a computer operated applications. This automatic summarization technique works in a computer to summarize the text inputted by user. A document entered into the computer application, then processed and summarized to produce a summary from original text. In research document extraction method used Maximum Marginal Relevance algorithm. MMR is a summary document extraction method is used to summarize a single document or multiple documents. MMR summarizing document by calculating the similarity between the sentences text in a paragraph. In this summarization contents for document segmentation process is carried out using a combination of gender-based matrix cosine similarity. Cosine similarity is used to calculate the relevance of the query approach on a document. The determination of relevance in a query against document is considered as measurement of similarity between queries with vectors of documents. The results from the automatic summary application is a sequential list words according to the results obtained algorithms. The closeness results with query assessed from the lambda limit values applied in the cosine similarity is 0 to 1.

Dibuat oleh : Jasman Pardede, Jordy Sinatria
E-mail : jasman@itenas.ac.id
Kata kunci :summarization, MMR, queries, similarity, cosine similarity.

Keterangan : Karya Ilmiah ini  dimuat pada Prosiding Konferensi Nasional Sistem Informasi KNSI 2015, 26 - 28 Februari 2015

<a href="http://lib.itenas.ac.id/kti/wp-content/uploads/2015/03/Text_Summarization_Maximum_Marginal_Relevance_Jasman_Pardede.pdf">IMPLEMENTASI MAXIMUM MARGINAL RELEVANCE DAN MATRIKS COSINE SIMILARITY PADA APLIKASI PERINGKASAN DOKUMEN</a>]]>"""^^rdf:XMLLiteral ;
  sioc:content """Automatic Text Summarization are sorting paragraphs into shorter forms using a computer operated applications. This automatic summarization technique works in a computer to summarize the text inputted by user. A document entered into the computer application, then processed and summarized to produce a summary from original text. In research document extraction method used Maximum Marginal Relevance algorithm. MMR is a summary document extraction method is used to summarize a single document or multiple documents. MMR summarizing document by calculating the similarity between the sentences text in a paragraph. In this summarization contents for document segmentation process is carried out using a combination of gender-based matrix cosine similarity. Cosine similarity is used to calculate the relevance of the query approach on a document. The determination of relevance in a query against document is considered as measurement of similarity between queries with vectors of documents. The results from the automatic summary application is a sequential list words according to the results obtained algorithms. The closeness results with query assessed from the lambda limit values applied in the cosine similarity is 0 to 1.

Dibuat oleh : Jasman Pardede, Jordy Sinatria
E-mail : jasman@itenas.ac.id
Kata kunci :summarization, MMR, queries, similarity, cosine similarity.

Keterangan : Karya Ilmiah ini  dimuat pada Prosiding Konferensi Nasional Sistem Informasi KNSI 2015, 26 - 28 Februari 2015

IMPLEMENTASI MAXIMUM MARGINAL RELEVANCE DAN MATRIKS COSINE SIMILARITY PADA APLIKASI PERINGKASAN DOKUMEN""" ;
  sioc:topic <http://lib.itenas.ac.id/kti/?cat=1>, <http://lib.itenas.ac.id/kti/?cat=7>, <http://lib.itenas.ac.id/kti/?tag=cosine-similarity>, <http://lib.itenas.ac.id/kti/?tag=mmr>, <http://lib.itenas.ac.id/kti/?tag=queries>, <http://lib.itenas.ac.id/kti/?tag=similarity>, <http://lib.itenas.ac.id/kti/?tag=summarization> ;
  sioc:attachment <http://lib.itenas.ac.id/kti/wp-content/uploads/2015/03/Text_Summarization_Maximum_Marginal_Relevance_Jasman_Pardede.pdf> .

<http://lib.itenas.ac.id/kti/?author=6#account> rdfs:seeAlso <http://lib.itenas.ac.id/kti/?author=6&feed=lhrdf&format=turtle> .
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<http://lib.itenas.ac.id/kti/?tag=cosine-similarity> rdfs:seeAlso <http://lib.itenas.ac.id/kti/?tag=cosine-similarity&feed=lhrdf&format=turtle> .
<http://lib.itenas.ac.id/kti/?tag=mmr> rdfs:seeAlso <http://lib.itenas.ac.id/kti/?tag=mmr&feed=lhrdf&format=turtle> .
<http://lib.itenas.ac.id/kti/?tag=queries> rdfs:seeAlso <http://lib.itenas.ac.id/kti/?tag=queries&feed=lhrdf&format=turtle> .
<http://lib.itenas.ac.id/kti/?tag=similarity> rdfs:seeAlso <http://lib.itenas.ac.id/kti/?tag=similarity&feed=lhrdf&format=turtle> .
<http://lib.itenas.ac.id/kti/?tag=summarization> rdfs:seeAlso <http://lib.itenas.ac.id/kti/?tag=summarization&feed=lhrdf&format=turtle> .
<http://lib.itenas.ac.id/kti/wp-content/uploads/2015/03/Text_Summarization_Maximum_Marginal_Relevance_Jasman_Pardede.pdf> rdfs:seeAlso <http://lib.itenas.ac.id/kti/?attachment_id=4239&feed=lhrdf&format=turtle> .