Extractive multi-document text summarization using dolphin swarm optimization approach

Autor: Alok Agarwal, Dhiraj Pandey, Atul Kumar Srivastava

Publikováno v: Multimedia Tools and Applications. 80:11273-11290

Nowadays, extracting the desired information from internet source is a challenging task because of a large amount of information available on the internet. So, we propose a new extractive based approach for multi-document text summarization to extrac

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::3ef55bb45557ddd0cf829679798dbe1d
https://doi.org/10.1007/s11042-020-10176-1

Automatic Keywords Extraction Based on Co-Occurrence and Semantic Relationships Between Words

Autor: Shaobin Huang, Li Rongsheng, Xiangke Mao, Linshan Shen

Publikováno v: IEEE Access, Vol 8, Pp 117528-117538 (2020)

Automatic keywords extraction is a method that extracts words or phrases from a document which can express the main idea of the document. In this paper, we propose an unsupervised keywords extraction framework for individual documents, which improves

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f57d0a26c209c4d34c422cedead9fafa
https://ieeexplore.ieee.org/document/9123849/

Development of a Cell Transmission Model Using Crowdsourced Data for Expressways

Autor: W.M.R.V. Wijepala, G.Ld.I. de Silva

Publikováno v: 2021 Moratuwa Engineering Research Conference (MERCon).

The demand for expressways in Sri Lanka is rapidly increasing with the increasing traffic congestion in alternate roads. Traffic management strategies have to be considered with further increase in demand for expressways. Deviating from traditional e

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::6dbdc87ba569b1a3463d49f22f873d90
https://doi.org/10.1109/mercon52712.2021.9525681

Result diversification in image retrieval based on semantic distance

Autor: Wei Lu, Mengqi Luo, Zhenyu Zhang, Heng Ding, Jiangping Chen, Guobiao Zhang, Haihua Chen

Publikováno v: Information Sciences. 502:59-75

User requirements for result diversification in image retrieval have been increasing with the explosion of image resources. Result diversification requires that image retrieval systems are made capable of handling semantic gaps between image visual f

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::4eea0810470d422024c2bcff6e77cdbb
https://doi.org/10.1016/j.ins.2019.06.020

Ontology-based methods for classifying scientific datasets into research domains: Much harder than expected

Autor: Wang, Xu, Van Harmelen, Frank, Huang, Zhisheng, Fred, Ana, Filipe, Joaquim

Publikováno v: Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management-KDIR: Volume 1, 1, 153-160
Wang, X, Van Harmelen, F & Huang, Z 2020, Ontology-based methods for classifying scientific datasets into research domains : Much harder than expected . in A Fred & J Filipe (eds), Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management-KDIR : Volume 1 . vol. 1, Proceedings of the International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, SciTePress, pp. 153-160, 12th International Conference on Knowledge Discovery and Information Retrieval, KDIR 2020-Part of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2020, Virtual, Online, 2/11/20 . https://doi.org/10.5220/0010056101530160
KDIR

Scientific datasets are increasingly stored, published, and re-used online. This has prompted major search engines to start services dedicated to finding research datasets online. However, to date such services are limited to keyword search, and prov

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6db64ec7ee3967dbc9906db2880da202
https://research.vu.nl/en/publications/8cfb26b0-1f29-4092-bf63-0806f62d73ab