Toward an enhanced Arabic text classification using cosine similarity and Latent Semantic Indexing
نویسندگان
چکیده
منابع مشابه
Big Data Categorization for Arabic Text Using Latent Semantic Indexing and Clustering
Documents categorization is an important field in the area of natural language processing. In this paper, we propose using Latent Semantic Indexing (LSI), singular value decomposing (SVD) method, and clustering techniques to group similar unlabeled document into pre-specified number of topics. The generated groups are then categorized using a suitable label. For clustering, we used Expectation–...
متن کاملSprinkled Latent Semantic Indexing for Text Classification with Background Knowledge
In text classification, one key problem is its inherent dichotomy of polysemy and synonym; the other problem is the insufficient usage of abundant useful, but unlabeled text documents. Targeting on solving these problems, we incorporate a sprinkling Latent Semantic Indexing (LSI) with background knowledge for text classification. The motivation comes from: 1) LSI is a popular technique for info...
متن کاملRelationship Discovery in Large Text Collections Using Latent Semantic Indexing
This paper addresses the problem of information discovery in large collections of text. For users, one of the key problems in working with such collections is determining where to focus their attention. In selecting documents for examination, users must be able to formulate reasonably precise queries. Queries that are too broad will greatly reduce the efficiency of information discovery efforts...
متن کاملGeneric Text Summarization Using Probabilistic Latent Semantic Indexing
This paper presents a strategy to generate generic summary of documents using Probabilistic Latent Semantic Indexing. Generally a document contains several topics rather than a single one. Summaries created by human beings tend to cover several topics to give the readers an overall idea about the original document. Hence we can expect that a summary containing sentences from better part of the ...
متن کاملLRLW-LSI: An Improved Latent Semantic Indexing (LSI) Text Classifier
The task of Text Classification (TC) is to automatically assign natural language texts with thematic categories from a predefined category set. And Latent Semantic Indexing (LSI) is a well known technique in Information Retrieval, especially in dealing with polysemy (one word can have different meanings) and synonymy (different words are used to describe the same concept), but it is not an opti...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of King Saud University - Computer and Information Sciences
سال: 2017
ISSN: 1319-1578
DOI: 10.1016/j.jksuci.2016.04.001