Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Samaresh Maiti"'
This article focuses on the importance of the continuous collection of water parameters data from the sensors and also the prediction of water quality using the latest different Machine learning algorithms like Logistic Regression, Random Forest, Sup
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3a2b4742c4dfbfd0a227a6072e39d93a
https://doi.org/10.36227/techrxiv.22300435.v1
https://doi.org/10.36227/techrxiv.22300435.v1
Autor:
Deboshree Modak, Sucharita Sanyal, Dipasree Pal, Mandar Mitra, Sukomal Pal, Samaresh Maiti, Ayan Bandyopadhyay, Prasenjit Majumder
Publikováno v:
ACM Transactions on Asian Language Information Processing. 9:1-24
The aim of the Forum for Information Retrieval Evaluation (FIRE) is to create an evaluation framework in the spirit of TREC (Text REtrieval Conference), CLEF (Cross-Language Evaluation Forum), and NTCIR (NII Test Collection for IR Systems), for India
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4555e46d2918484e2446e78d82be2b21
https://doi.org/10.1145/1838745.1838747
https://doi.org/10.1145/1838745.1838747
Autor:
Aparajita Sen, Samaresh Maiti, Sukomal Pal, Sukanya Mitra, Debasis Ganguly, Mandar Mitra, Ayan Bandyopadhyay
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783642037603
INEX
INEX
This paper describes the work that we did at Indian Statistical Institute towards XML retrieval for INEX 2008. Besides the Vector Space Model (VSM) that we have been using since INEX 2006, this year we implemented the Language Modeling (LM) approach
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e2dd1b3aa29c7adec7a3816594bc0e7d
https://doi.org/10.1007/978-3-642-03761-0_9
https://doi.org/10.1007/978-3-642-03761-0_9
Autor:
Mandar Mitra, Aparajita Sen, Samaresh Maiti, Prasenjit Majumder, Sukanya Mitra, Dipasree Pal, Ayan Bandyopadhyay, Sukomal Pal
Publikováno v:
SIGIR
The aim of the Forum for Information Retrieval Evaluation (FIRE) is to create a Cranfield-like evaluation framework in the spirit of TREC, CLEF and NTCIR, for Indian Language Information Retrieval. For the first year, six Indian languages have been s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d144f4fb3b3a99cc55aca9770ed486e3
https://doi.org/10.1145/1390334.1390458
https://doi.org/10.1145/1390334.1390458