Toward the Next Generation of Recommender Systems: Applications and Research Challenges

2013 ◽  
pp. 81-98 ◽  
Author(s):  
Alexander Felfernig ◽  
Michael Jeran ◽  
Gerald Ninaus ◽  
Florian Reinfrank ◽  
Stefan Reiterer
Keyword(s):  
Recommender Systems ◽  
Next Generation ◽  
Research Challenges

New Directions in Social Question Answering

2013 ◽  
pp. 266-284
Author(s):  
Mohan John Blooma ◽  
Jayan Chirayath Kurian
Keyword(s):  
Question Answering ◽  
Information Resource ◽  
Next Generation ◽  
Social Question ◽  
Information Richness ◽  
Research Challenges ◽  
New Directions ◽  
Question Answering Systems ◽  
Research Stream ◽  
Research Domains

Social Question Answering (SQA) services are emerging as a valuable information resource that is rich not only in the expertise of the user community but also their interactions and insights. The next generation SQA services are challenged in many fronts, including but not limited to: massive, heterogeneous, and streaming collections, diverse and challenging users, and the need to be sensitive to context and ambiguity. However, scholarly inquiries have yet to dovetail into a composite research stream where techniques gleaned from various research domains could be used for harnessing the information richness in SQA services to address these challenges. This chapter first explores the SQA domain by understanding the service and its modules, and then investigating previous studies that were conducted in this domain. This chapter then compares SQA services with traditional question answering systems to identify possible research challenges. Finally, new directions in SQA are proposed.

A Survey of Multimedia Recommender Systems: Challenges and Opportunities

2017 ◽  
Vol 11 (03) ◽  
pp. 411-428 ◽  
Author(s):  
Mouzhi Ge ◽  
Fabio Persia
Keyword(s):  
Multimedia Information ◽  
Recommender Systems ◽  
Recommender System ◽  
Future Research ◽  
Research Directions ◽  
Research Challenges ◽  
Challenges And Opportunities ◽  
Future Research Directions ◽  
Research Challenge

Multimedia information has been extensively growing from a variety of sources such as cameras or video recorders. In order to select the useful multimedia objects, multimedia recommender system has been emerging as a tool to help users choose which multimedia objects might be interesting for them. However, given the complexity of multimedia objects, it is challenging to provide effective multimedia recommendations. In this paper, we therefore conduct a survey in both the multimedia information system and recommender system communities. We further focus on the works that span the two communities, especially the research on multimedia recommender systems. Based on our review, we propose a set of research challenges, which can be used to implicate the future research directions for multimedia recommender systems. For each research challenge, we have also provided the insights of how to perform the follow-up research.

Sign in / Sign up

Export Citation Format

Share Document