Information Retrieval and Natural Language Processing

This book gives a comprehensive view of graph theory in informational retrieval (IR) and natural language processing(NLP). This book provides number of graph techniques for IR and NLP applications with examples. It also provides understanding of graph theory basics, graph algorithms and networks using graph. The book is divided into three parts and contains nine chapters. The first part gives graph theory basics and graph networks, and the second part provides basics of IR with graph-based information retrieval. The third part covers IR and NLP recent and emerging applications with case studies using graph theory.

This book is unique in its way as it provides a strong foundation to a beginner in applying mathematical structure graph for IR and NLP applications. All technical details that include tools and technologies used for graph algorithms and implementation in Information Retrieval and Natural Language Processing with its future scope are explained in a clear and organized format.

Autorentext

Dr. Sheetal S. Sonawane is an associate professor in the Department of Computer Engineering at Pune institute of Computer Technology (Pune). She received PhD in Computer Engineering from college of Engineering at Savitribai Phule Pune University in 2018. She received her bachelor's degree in computer engineering from Pune University in 2000 and 4th rank holder in Pune University for master's degree in computer engineering in year 2006. She has more than 19 years of teaching and research experience. She has published widely in international journals like Springer, Inderscience and conferences like IEEE, Springer and having more than 615 citations. She is a recipient of Best Paper Award for her IEEE Conference paper. She has written book chapters in books like Big data analytics by PHI Publication and Semigraph and their applications by academy of discrete mathematics and applications, India. She is an author of book Foundations of Data Science Based Healthcare Internet of Things by Springer. She is reviewer of conferences and journals like IEEE, Elsevier, MDPI Journal, Inderscience, etc. She has published three Indian Patents out of which 2 are granted. She has delivered talks on national level. She has also remained a technical program committee member and session chair for international conferences. She is involved as coordinator for Data Science Honors course at SPPU and syllabus coordinator for many subjects at University level. Her research interest is in the field of Information retrieval, Natural Language processing and Data Mining. She has focused in the last few years on the research issued in machine learning, handling big unstructured data and graph model for representing and analyzing text documents.

Dr. Parikshit N. Mahalle obtained his B.E degree in Computer Science and Engineering from Sant Gadge Baba Amravati University, Amravati, India, and ME degree in Computer Engineering from Savitribai Phule Pune University, Pune, India. He completed his PhD in Computer Science and Engineering specialization in Wireless Communication from Aalborg University, Aalborg, Denmark. He was a postdoctoral researcher at CMI, Aalborg University, Copenhagen, Denmark. Currently, he worked as a professor and the head in the Department of Computer Engineering at STES's Smt. Kashibai Navale College of Engineering, Pune, India, since 2005 to June 2021. Currently, he is working as a professor and the head in the Department of Artificial intelligence and Data Science, Vishwakarma Institute of Information Technology, Pune, India. He has more than 21 years of teaching and research experience. He is serving as a subject expert in Computer Engineering, Research and Recognition Committee at several universities like SPPU (Pune), SGBU (Amravati). He is a senior member IEEE, ACM member, Life member CSI and Life member ISTE. Also, he is a member of IEEE transaction on Information Forensics and Security, IEEE Internet of Things Journal. He is a reviewer for IGI Global committee member for international conferences and symposium like IEEE ICC, IEEE INDICON, IEEE GCWSN, IEEE ICCUBEA, etc. He is a reviewer for the Springer Journal of Wireless Personal Communications, reviewer for Elsevier Journal of Applied Computing and Informatics, member of the Editorial Review Board of IGI Global International Journal of Ambient Computing and Intelligence (IJACI), member of the Editorial Review Board for Journal of Global Research in Computer Science. He has published more than 190 research publications having 1900+ citations and H index 18. He has 7 edited books to his credit by Springer and CRC Press. He has 7 patents to his credit. He has also delivered invited talk on Identity Management in IoT to Symantec Research Lab, Mountain View, California. He has delivered more than 100 lectures at national and international level on IoT, big data and digitization. He has authored 15 books on subjects like Context-aware Pervasive Systems and Application (Springer Nature Press), Design and Analysis of Algorithms (Cambridge International Journal of Rough Sets and Data Analysis (IJRSDA), Associate Editor for IGI Global International Journal of Synthetic Emotions (IJSE), International Journal of Grid and Utility Computing (IJGUC). He is a Member-Editorial Review Board for IGI Global International Journal of Ambient Computing and Intelligence (IJACI). He is also working as an Associate Editor for IGI Global - International Journal of Synthetic Emotions (IJSE). He has also remained a technical program University), Identity Management for the Internet of Things (River Publications), Data Structure and Algorithms (Cengage Publications), Programming using Python (Tech- Neo Publications MSBTE). He had worked as Chairman of Board of Studies (Information Techno...

Inhalt
Part A.- Chapter 1. Graph theory basics.- Chapter 2. Graph Algorithms.- Chapter 3. Networks using graph.- Part B.- Chapter 4. Information retrieval.- Chapter 5. Text document preprocessing using graph theory.- Chapter 6. Text analytics using graph theory.- Chapter 7. Knowledge graph.- Part C.- Chapter 8. Emerging Applications and development.- Chapter 9. Conclusion and future scope.