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Nilupulee Nathawitharana,Damminda Alahakoon,Sumith Matharage
Humans are used to expressing themselves with written language and language provides a medium with which we can describe our experiences in detail incorporating individuality. Even though documents provide a rich source of information, it becomes very di...
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Laith Abualigah, Amir H. Gandomi, Mohamed Abd Elaziz, Abdelazim G. Hussien, Ahmad M. Khasawneh, Mohammad Alshinwan and Essam H. Houssein
Text clustering is one of the efficient unsupervised learning techniques used to partition a huge number of text documents into a subset of clusters. In which, each cluster contains similar documents and the clusters contain dissimilar text documents. Na...
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Samuel R. Schrader and Eren Gultepe
The evaluation of similarities between natural languages often relies on prior knowledge of the languages being studied. We describe three methods for building phylogenetic trees and clustering languages without the use of language-specific information. ...
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Gabriele Papadia, Massimo Pacella and Vincenzo Giliberti
This paper focuses on the automatic analysis of conversation transcriptions in the call center of a customer care service. The goal is to recognize topics related to problems and complaints discussed in several dialogues between customers and agents. Our...
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Min-Hsien Weng, Shaoqun Wu and Mark Dyer
With the rapidly growing number of scientific publications, researchers face an increasing challenge of discovering the current research topics and methodologies in a scientific domain. This paper describes an unsupervised topic detection approach that u...
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Oleksii Kungurtsev,Svitlana Zinovatna,Iana Potochniak,Nataliia Novikova
Pág. 39 - 47
The aim of research is to improve the quality of domain dictionaries by expanding the corpus of the documents under study by using short documents. A document model is proposed that allows to define a short document and the need to combine it with other ...
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Nan Xing, Jianqi Zhang, Furong Cao and Pengfei Liu
When recovering a shredded document that has numerous mixed pieces, the difficulty of the recovery process can be reduced by clustering, which is a method of grouping pieces that originally belonged to the same page. Restoring homologous shredded documen...
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Shariq Bashir
Cluster-based pseudo-relevance feedback (PRF) is an effective approach for searching relevant documents for relevance feedback. Standard approach constructs clusters for PRF only on the basis of high similarity between retrieved documents. The standard a...
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Lukas Busch, Ruben van Heusden and Maarten Marx
Page stream segmentation (PSS) is the task of retrieving the boundaries that separate source documents given a consecutive stream of documents (for example, sequentially scanned PDF files). The task has recently gained more interest as a result of the di...
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Georgios Drakopoulos, Andreas Kanavos, Ioannis Karydis, Spyros Sioutas and Aristidis G. Vrahatis
Biomedicine is a pillar of the collective, scientific effort of human self-discovery, as well as a major source of humanistic data codified primarily in biomedical documents. Despite their rigid structure, maintaining and updating a considerably-sized co...
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Hongyu Shao, Sizhe Pan, Yufei Song and Quanfu Li
In the context of rapid product iteration, design conflicts arise from discrepancies in designers? understanding of user needs, influenced by subjective preferences, behavioural stances, and other factors. This paper proposes a product conceptual design ...
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Abdelrhman Eldallal and Eduard Barbu
Automatic Keyphrase Extraction involves identifying essential phrases in a document. These keyphrases are crucial in various tasks, such as document classification, clustering, recommendation, indexing, searching, summarization, and text simplification. ...
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Benjamin Shade and Eduardo G. Altmann
Quantifying the dissimilarity of two texts is an important aspect of a number of natural language processing tasks, including semantic information retrieval, topic classification, and document clustering. In this paper, we compared the properties and per...
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Sergey Gorshkov,Eugene Ilyushin,Anastasia Chernysheva,Viacheslav Goiko,Dmitry Namiot
Pág. 12 - 17
Topic modeling is one of the most widely used methods in text analysis. It can be used to select topics as well as to find the topics distributed in each document from the corpus. In this article, we present a method for clustering co...
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Mausumi Goswami,B.S Purkayastha
With fast growth in size of digital text documents over internet and digital repositories, the pools of digital document is piling up day by day. Due to this digital revolution and growth, an efficient and effective technique is required to handle such a...
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Zhenzhou Xu, Ge Cui, Ming Zhong and Xin Wang
Anomalous urban mobility pattern refers to abnormal human mobility flow in a city. Anomalous urban mobility pattern detection is important in the study of urban mobility. In this paper, a framework is proposed to identify anomalous urban mobility pattern...
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?tefan Ionescu, Camelia Delcea, Nora Chiri?a and Ionu? Nica
This research provides a comprehensive analysis of the dynamic interplay between agent-based modeling (ABM) and artificial intelligence (AI) through a meticulous bibliometric study. This study reveals a substantial increase in scholarly interest, particu...
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Liliya Demidova, Dmitry Zhukov, Elena Andrianova and Vladimir Kalinin
To solve the problem of text clustering according to semantic groups, we suggest using a model of a unified lexico-semantic bond between texts and a similarity matrix based on it. Using lexico-semantic analysis methods, we can create ?term?document? matr...
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Chunchun Hu, Qin Liang, Nianxue Luo and Shuixiang Lu
Analysis of the spatiotemporal distribution of online public opinion topics can help understand the hotspots of public concern. The topic model is employed widely in public opinion topic clustering for social media data. In order to handle topic-clusteri...
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Dauren Ayazbayev, Andrey Bogdanchikov, Kamila Orynbekova and Iraklis Varlamis
This work focuses on determining semantically close words and using semantic similarity in general in order to improve performance in information retrieval tasks. The semantic similarity of words is an important task with many applications from informati...
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