An approach based on combination of Features for automatic news retrieval
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@Article{JICS-14-279,
author = {JingjiZhao},
title = {An approach based on combination of Features for automatic news retrieval},
journal = {Journal of Information and Computing Science},
year = {2024},
volume = {14},
number = {4},
pages = {279--290},
abstract = {1 Department of Computer Engineering, Yadegar-e-Imam Khomeini (RAH) Shahr-e-Rey Branch, Islamic Azad
University, Tehran, Iran
2 Department of Computer Engineering, Karaj Branch, Islamic Azad University, Karaj, Iran
(Received October 15 2019, accepted December 26 2019)
Nowadays, according to the increasingly increasing information, the importance of its presentation
is also increasing. The internet has become one of the main sources of information for users and their favorite
topics. It also provides access to more information. Understanding this information is very important for
providing the best set of information resources for users. Content providers now need a precise and efficient
way to retrieve news with the least human help. Data mining has led to the emergence of new methods for
detecting related and unrelated documents. Although the conceptual relationship between documents may be
negligible, it is important to provide useful information and relevant content to users. In this paper, a new
approach based on the Combination of Features (CoF) for information retrieval operations is introduced. Along
with introducing this new approach, we proposed a dataset by identifying the most commonly used keywords
in documents and using the most appropriate documents to help them with the abundance of vocabulary. Then,
using the proposed approach, techniques of text categorization, evaluation criteria and ranking algorithms, the
data were analyzed and examined. The evaluation results show that using the combination of features approach
improves the quality and effects on efficient ranking.
},
issn = {1746-7659},
doi = {https://doi.org/},
url = {http://global-sci.org/intro/article_detail/jics/22404.html}
}
TY - JOUR
T1 - An approach based on combination of Features for automatic news retrieval
AU - JingjiZhao
JO - Journal of Information and Computing Science
VL - 4
SP - 279
EP - 290
PY - 2024
DA - 2024/01
SN - 14
DO - http://doi.org/
UR - https://global-sci.org/intro/article_detail/jics/22404.html
KW - Information retrieval, news retrieval, combination of features, ranking news, dataset, benchmark
dataset.
AB - 1 Department of Computer Engineering, Yadegar-e-Imam Khomeini (RAH) Shahr-e-Rey Branch, Islamic Azad
University, Tehran, Iran
2 Department of Computer Engineering, Karaj Branch, Islamic Azad University, Karaj, Iran
(Received October 15 2019, accepted December 26 2019)
Nowadays, according to the increasingly increasing information, the importance of its presentation
is also increasing. The internet has become one of the main sources of information for users and their favorite
topics. It also provides access to more information. Understanding this information is very important for
providing the best set of information resources for users. Content providers now need a precise and efficient
way to retrieve news with the least human help. Data mining has led to the emergence of new methods for
detecting related and unrelated documents. Although the conceptual relationship between documents may be
negligible, it is important to provide useful information and relevant content to users. In this paper, a new
approach based on the Combination of Features (CoF) for information retrieval operations is introduced. Along
with introducing this new approach, we proposed a dataset by identifying the most commonly used keywords
in documents and using the most appropriate documents to help them with the abundance of vocabulary. Then,
using the proposed approach, techniques of text categorization, evaluation criteria and ranking algorithms, the
data were analyzed and examined. The evaluation results show that using the combination of features approach
improves the quality and effects on efficient ranking.
JingjiZhao. (2024). An approach based on combination of Features for automatic news retrieval.
Journal of Information and Computing Science. 14 (4).
279-290.
doi:
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