Anuradha D Thakare, Shilpa Laddha, Ambika Pawar
Hybrid Intelligent Systems for Information Retrieval (eBook, PDF)
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Anuradha D Thakare, Shilpa Laddha, Ambika Pawar
Hybrid Intelligent Systems for Information Retrieval (eBook, PDF)
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The book covers three areas along with the introduction to Intelligent IR, i.e. Optimal Information Retrieval using Evolutionary approaches, Semantic Search for Web Information Retrieval and Natural Language Processing for Information Retrieval.
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The book covers three areas along with the introduction to Intelligent IR, i.e. Optimal Information Retrieval using Evolutionary approaches, Semantic Search for Web Information Retrieval and Natural Language Processing for Information Retrieval.
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Produktdetails
- Produktdetails
- Verlag: Taylor & Francis
- Seitenzahl: 252
- Erscheinungstermin: 22. November 2022
- Englisch
- ISBN-13: 9781000783322
- Artikelnr.: 65737226
- Verlag: Taylor & Francis
- Seitenzahl: 252
- Erscheinungstermin: 22. November 2022
- Englisch
- ISBN-13: 9781000783322
- Artikelnr.: 65737226
- Herstellerkennzeichnung Die Herstellerinformationen sind derzeit nicht verfügbar.
Anuradha D Thakare is a Professor in Department of Computer Engineering in Pimpri Chinchwad College of Engineering, Pune. She has more than 22 years of teaching and research experience. Anuradha received her Ph.D in Computer Science and Engineering from SGB Amravati University, M.E. degree in Computer Engineering from Savitribai Phule Pune University and BE degree in Computer Science and Engineering from Sant Gadge Baba Amravati University, Amravati, India. Her area of research includes Artificial Intelligence, Machine Learning, Healthcare Data Analytics, Evolutionary Computing etc. She is PhD guide in Computer Engineering in SPPU, Pune. Dr. Anuradha worked as Secretary of Institution of engineering & Technology Pune LN, Member of IEEE and ACM.
Dr. Anuradha has published 95 research papers in reputed Journals and Conferences with indexing in SCI, Scopus, IEEE, Web of Science, Elsevier and Springer etc. She has authored and edited books published by CRC Taylor & Francis, IGI Global, Scrivener-Wiley etc. She received Research project grant and workshop grants from AICTE-AQIS, QIP-SPPU, BCUD-SPPU Pune and Maharashtra State Commission for Women. She Received Best Women Researcher Award and Best Faculty Award from International Forum on Science, Health & Engineering. She received best paper award in International Conferences. Delivered 26 expert talks on Machine Learning, Evolutionary Algorithms, Outcome Based Education etc. she worked with industries like DRDO, NCL etc for research projects.She has been a General Chair of IEEE International Conference ICCUBEA 2018 and Advisory member for International Conferences. She worked as reviewer for Journal of International Blood Research, IEEE transactions and Scopus Journals.
Dr. Shilpa Laddha is an Assistant Professor in Department of Information Technology at Government College of Engineering, Aurangabad. Prof. Laddha has completed her Bachelors Degree and Masters Degree in Computer Science & Engineering from SGBAU, Amravati and Dr. BAMU, Aurangabad, India respectively. She did her Doctorate in Computer Science & Engineering from Sant Gadge Baba Amravati University (SGBAU), Amravati, India. She is PhD guide in Computer Engineering in Dr. Babasaheb Ambedkar Marathwada University. She has more than 22 years of teaching and research experience.
Her area of interest includes Artificial Intelligence, Machine Learning, Information Retrieval, Semantic Web Mining & Ontology and many more. She has a profound expertise in taking the full depth training of engineering students. She has authored one book. She has Two Copyrights and three patents to her credit & her many research papers are published in prominent international journals.
She has presented research communications in national and international meetings and a visiting professor to many universities. She is reviewer for various Journals & Conferences. She has guided more than 200 students for their graduation projects. She is associated with the development of an innovative, integrated engineering curriculum designing for various colleges. She received Outstanding Women (Computer Science & Engineering) Award VIWA 2020 by the Centre for Advanced Research and Design, Venus International Foundation, Chennai. She also received International Excellence "Best Research Thesis" Award at 1st Universal Innovators Leadership Awards (UILA 2020) by :SScbs, University of Delhi, New Delhi in association with NIT Patna & University of Valladolid, Spain
Dr. Ambika Pawar is an Associate Professor in Computer Science & Engineering and Information Technology Department, Symbiosis Institute of Technology, Symbiosis International (Deemed University), Pune, India.
She has obtained her B.E. degree in Computer Science and Engineering from Pune University, Pune, India and M.E. degree in Computer Engineering from Pune University, Pune, India. She completed her Ph.D in Computer Science and Engineering from Symbiosis International (Deemed University). She has more than 18 years of teaching and research experience. Dr. Ambika is guiding total seven PHD scholars in Computer Engineering at Symbiosis International (Deemed University) & Lovely Professional University. She worked as Tutorial Chair of IEEE International Conference IEEE PUNECON 2018. She has 32 Publications in reputed Journals & conference with indexing in Scopus, IEEE, Web of Science, Elsevier, Springer. She worked as reviewer and session chairs for International Conferences. Delivered expert talks on Data Privacy, Analysis of Algorithms, Cloud Computing etc.
Dr. Anuradha has published 95 research papers in reputed Journals and Conferences with indexing in SCI, Scopus, IEEE, Web of Science, Elsevier and Springer etc. She has authored and edited books published by CRC Taylor & Francis, IGI Global, Scrivener-Wiley etc. She received Research project grant and workshop grants from AICTE-AQIS, QIP-SPPU, BCUD-SPPU Pune and Maharashtra State Commission for Women. She Received Best Women Researcher Award and Best Faculty Award from International Forum on Science, Health & Engineering. She received best paper award in International Conferences. Delivered 26 expert talks on Machine Learning, Evolutionary Algorithms, Outcome Based Education etc. she worked with industries like DRDO, NCL etc for research projects.She has been a General Chair of IEEE International Conference ICCUBEA 2018 and Advisory member for International Conferences. She worked as reviewer for Journal of International Blood Research, IEEE transactions and Scopus Journals.
Dr. Shilpa Laddha is an Assistant Professor in Department of Information Technology at Government College of Engineering, Aurangabad. Prof. Laddha has completed her Bachelors Degree and Masters Degree in Computer Science & Engineering from SGBAU, Amravati and Dr. BAMU, Aurangabad, India respectively. She did her Doctorate in Computer Science & Engineering from Sant Gadge Baba Amravati University (SGBAU), Amravati, India. She is PhD guide in Computer Engineering in Dr. Babasaheb Ambedkar Marathwada University. She has more than 22 years of teaching and research experience.
Her area of interest includes Artificial Intelligence, Machine Learning, Information Retrieval, Semantic Web Mining & Ontology and many more. She has a profound expertise in taking the full depth training of engineering students. She has authored one book. She has Two Copyrights and three patents to her credit & her many research papers are published in prominent international journals.
She has presented research communications in national and international meetings and a visiting professor to many universities. She is reviewer for various Journals & Conferences. She has guided more than 200 students for their graduation projects. She is associated with the development of an innovative, integrated engineering curriculum designing for various colleges. She received Outstanding Women (Computer Science & Engineering) Award VIWA 2020 by the Centre for Advanced Research and Design, Venus International Foundation, Chennai. She also received International Excellence "Best Research Thesis" Award at 1st Universal Innovators Leadership Awards (UILA 2020) by :SScbs, University of Delhi, New Delhi in association with NIT Patna & University of Valladolid, Spain
Dr. Ambika Pawar is an Associate Professor in Computer Science & Engineering and Information Technology Department, Symbiosis Institute of Technology, Symbiosis International (Deemed University), Pune, India.
She has obtained her B.E. degree in Computer Science and Engineering from Pune University, Pune, India and M.E. degree in Computer Engineering from Pune University, Pune, India. She completed her Ph.D in Computer Science and Engineering from Symbiosis International (Deemed University). She has more than 18 years of teaching and research experience. Dr. Ambika is guiding total seven PHD scholars in Computer Engineering at Symbiosis International (Deemed University) & Lovely Professional University. She worked as Tutorial Chair of IEEE International Conference IEEE PUNECON 2018. She has 32 Publications in reputed Journals & conference with indexing in Scopus, IEEE, Web of Science, Elsevier, Springer. She worked as reviewer and session chairs for International Conferences. Delivered expert talks on Data Privacy, Analysis of Algorithms, Cloud Computing etc.
1. Introduction. 2. Matching Functions. 3. Information Retrieval Models. 4. Hybrid Swarm Intelligence Approaches for Optimal Information Retrieval. 5. Information Retrieval and Semantic Search. 6. Ontology Creation using Clustering Technique. 7. Natural Language Processing for Information Retrieval. 8. Deep learning (DL) for Information retrieval (IR). 9. Application of Ontology in Domain Specific Information Retrieval: A case study. 10. Applications of Natural Language Processing and Information Retrieval.
1. Introduction. 2. Matching Functions. 3. Information Retrieval Models. 4.
Hybrid Swarm Intelligence Approaches for Optimal Information Retrieval. 5.
Information Retrieval and Semantic Search. 6. Ontology Creation using
Clustering Technique. 7. Natural Language Processing for Information
Retrieval. 8. Deep learning (DL) for Information retrieval (IR). 9.
Application of Ontology in Domain Specific Information Retrieval: A case
study. 10. Applications of Natural Language Processing and Information
Retrieval.
Hybrid Swarm Intelligence Approaches for Optimal Information Retrieval. 5.
Information Retrieval and Semantic Search. 6. Ontology Creation using
Clustering Technique. 7. Natural Language Processing for Information
Retrieval. 8. Deep learning (DL) for Information retrieval (IR). 9.
Application of Ontology in Domain Specific Information Retrieval: A case
study. 10. Applications of Natural Language Processing and Information
Retrieval.
1. Introduction. 2. Matching Functions. 3. Information Retrieval Models. 4. Hybrid Swarm Intelligence Approaches for Optimal Information Retrieval. 5. Information Retrieval and Semantic Search. 6. Ontology Creation using Clustering Technique. 7. Natural Language Processing for Information Retrieval. 8. Deep learning (DL) for Information retrieval (IR). 9. Application of Ontology in Domain Specific Information Retrieval: A case study. 10. Applications of Natural Language Processing and Information Retrieval.
1. Introduction. 2. Matching Functions. 3. Information Retrieval Models. 4.
Hybrid Swarm Intelligence Approaches for Optimal Information Retrieval. 5.
Information Retrieval and Semantic Search. 6. Ontology Creation using
Clustering Technique. 7. Natural Language Processing for Information
Retrieval. 8. Deep learning (DL) for Information retrieval (IR). 9.
Application of Ontology in Domain Specific Information Retrieval: A case
study. 10. Applications of Natural Language Processing and Information
Retrieval.
Hybrid Swarm Intelligence Approaches for Optimal Information Retrieval. 5.
Information Retrieval and Semantic Search. 6. Ontology Creation using
Clustering Technique. 7. Natural Language Processing for Information
Retrieval. 8. Deep learning (DL) for Information retrieval (IR). 9.
Application of Ontology in Domain Specific Information Retrieval: A case
study. 10. Applications of Natural Language Processing and Information
Retrieval.