Výsledky vyhledávání - "Mohsen Pourvali"

Akademický článek

Topic Models and Fusion Methods: a Union to Improve Text Clustering and Cluster Labeling

Autor: Mohsen Pourvali, Salvatore Orlando, Hosna Omidvarborna

Publikováno v: International Journal of Interactive Multimedia and Artificial Intelligence, Vol 5, Iss 4, Pp 28-34 (2019)

Topic modeling algorithms are statistical methods that aim to discover the topics running through the text documents. Using topic models in machine learning and text mining is popular due to its applicability in inferring the latent topic structure o

Externí odkaz: https://doaj.org/article/ea735aa30d764f7f85d832fff735c8a3

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Knowledge Mining: A Cross-disciplinary Survey

Autor: Yong Rui, Vicente Ivan Sanchez Carmona, Mohsen Pourvali, Yun Xing, Wei-Wen Yi, Hui-Bin Ruan, Yu Zhang

Publikováno v: Machine Intelligence Research. 19:89-114

Knowledge mining is a widely active research area across disciplines such as natural language processing (NLP), data mining (DM), and machine learning (ML). The overall objective of extracting knowledge from data source is to create a structured repr

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::f4f9927e75725c3b030670a1a39c327c
https://doi.org/10.1007/s11633-022-1323-6

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Topic Models and Fusion Methods: a Union to Improve Text Clustering and Cluster Labeling

Autor: Hosna Omidvarborna, Mohsen Pourvali, Salvatore Orlando

Publikováno v: International Journal of Interactive Multimedia and Artificial Intelligence, Vol 5, Iss 4, Pp 28-34 (2019)
Re-Unir. Archivo Institucional de la Universidad Internacional de La Rioja
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Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::305b18beffea0a772fb745c0526228db
http://www.ijimai.org/journal/node/2784

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Detecting Covariate Drift with Explanations

Autor: Steffen Castle, Robert Schwarzenberg, Mohsen Pourvali

Publikováno v: Natural Language Processing and Chinese Computing ISBN: 9783030884826
NLPCC (2)

Detecting when there is a domain drift between training and inference data is important for any model evaluated on data collected in real time. Many current data drift detection methods only utilize input features to detect domain drift. While effect

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::a85f9d8b87fdd1740a1a5320624d3fdb
https://doi.org/10.1007/978-3-030-88483-3_24

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Path-Based Visual Explanation

Autor: Yao Meng, Yucheng Jin, Mohsen Pourvali, Lei Wang, Changjian Hu, Masha Gorkovenko, Chen Sheng

Publikováno v: Natural Language Processing and Chinese Computing ISBN: 9783030604561
NLPCC (2)

The ability to explain the behavior of a Machine Learning (ML) model as a black box to people is becoming essential due to wide usage of ML applications in critical areas ranging from medicine to commerce. Case-Based Reasoning (CBR) received a specia

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::1dbc5dd9038aecc25b166102b56918cd
https://doi.org/10.1007/978-3-030-60457-8_37

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Enriching Documents by Linking Salient Entities and Lexical-Semantic Expansion

Autor: Mohsen Pourvali, Salvatore Orlando

Publikováno v: Journal of Intelligent Systems, Vol 29, Iss 1, Pp 1109-1121 (2018)

This paper explores a multi-strategy technique that aims at enriching text documents for improving clustering quality. We use a combination of entity linking and document summarization in order to determine the identity of the most salient entities m

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5814d97c0b59b0b73f82eaab54a72bd3
http://hdl.handle.net/10278/3711322

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Improving clustering quality by automatic text summarization

Autor: Salvatore Orlando, Mohsen Pourvali, Mehrad Gharagozloo

Publikováno v: Information Retrieval Technology ISBN: 9783319289397
AIRS

Automatic text summarization is the process of reducing the size of a text document, to create a summary that retains the most important points of the original document. It can thus be applied to summarize the original document by decreasing the impo

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dc1abeb4799a76705ba83fae735d10d8
http://hdl.handle.net/10278/3670250

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A new graph based text segmentation using Wikipedia for automatic text summarization

Autor: Mohsen Pourvali, Ph.D. Mohammad

Publikováno v: International Journal of Advanced Computer Science and Applications. 3

The technology of automatic document summarization is maturing and may provide a solution to the information overload problem. Nowadays, document summarization plays an important role in information retrieval. With a large volume of documents, presen

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::e305074771fe578a792d861ec7bf7518
https://doi.org/10.14569/ijacsa.2012.030105

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