The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Problems-Solving Map Extraction with Collective Intelligence Analysis and Language Engineering
Abstract
Valuable knowledge has been distributed in heterogeneous formats on many different Web sites and other sources over the Internet. However, finding the needed information is a complex task since there is a lack of semantic relations and organization between them. This chapter presents a problem-solving map framework for extracting and integrating knowledge from unstructured documents on the Internet by exploiting the semantic links between problems, methods for solving them and the people who could solve them. This challenging area of research needs both complex natural language processing, including deep semantic relation interpretation, and the participation of end-users for annotating the answers scattered on the Web. The framework is evaluated by generating problem solving maps for rice and human diseases.
Related Content
|
Rahul Kumar, Devvret Verma, Bahman Khoshru, Adeyemi Nurudeen Olatunbosun.
© 2026.
36 pages.
|
|
S. Ida Evangeline.
© 2026.
34 pages.
|
|
Rahul Kumar, Rachan Karmakar, Sanja Živković, Tanja Vasić.
© 2026.
42 pages.
|
|
Poonam K. Verma, Nisha Chandran.
© 2026.
20 pages.
|
|
Odangowei Inetiminebi Ogidi, Shoheb Shakil Shaikh, Mukul Machhindra Barwant.
© 2026.
42 pages.
|
|
Harsh Virendrabhai Purohit, Veda Pandya.
© 2026.
30 pages.
|
|
Rachan Karmakar, Divya Gunsola, Debasis Mitra, Viralkumar B. Mandaliya, Arti Thakur, Addisu Assefa, Sourav Chattaraj, Mukul Machhindra Barwant, Uma Eswaranpillai, Ponmurugan Karuppiah.
© 2026.
28 pages.
|
|
|