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 review of public datasets in question answering research

2020 ◽  
Vol 54 (2) ◽  
pp. 1-23
Author(s):  
B. Barla Cambazoglu ◽  
Mark Sanderson ◽  
Falk Scholer ◽  
Bruce Croft
Keyword(s):  
Question Answering ◽  
State Of The Art ◽  
Related Research ◽  
Current State ◽  
Research Challenges ◽  
Question Answering Systems ◽  
Faceted Classification ◽  
Public Datasets ◽  
Recent Evaluation

Recent years have seen an increase in the number of publicly available datasets that are released to foster research in question answering systems. In this work, we survey the available datasets and also provide a simple, multi-faceted classification of those datasets. We further survey the most recent evaluation results that form the current state of the art in question answering research by exploring related research challenges and associated online leaderboards. Finally, we provide a discussion around the existing online challenges and provide a wishlist of datasets whose release could benefit question answering research in the future.

scholarly journals A framework for enriching Data Warehouse analysis with Question Answering systems

2014 ◽  
Vol 46 (1) ◽  
pp. 61-82 ◽  
Author(s):  
Antonio Ferrández ◽  
Alejandro Maté ◽  
Jesús Peral ◽  
Juan Trujillo ◽  
Elisa De Gregorio ◽  
...  
Keyword(s):  
Data Warehouse ◽  
Question Answering ◽  
Question Answering Systems

scholarly journals Composing Questions through Conceptual Authoring

2007 ◽  
Vol 33 (1) ◽  
pp. 105-133 ◽  
Author(s):  
Catalina Hallett ◽  
Donia Scott ◽  
Richard Power
Keyword(s):  
Natural Language ◽  
Question Answering ◽  
Free Text ◽  
Risk Averse ◽  
Proof Of Concept ◽  
Concept System ◽  
Complex Queries ◽  
Extensive Training ◽  
Question Answering Systems ◽  
Medical Histories

This article describes a method for composing fluent and complex natural language questions, while avoiding the standard pitfalls of free text queries. The method, based on Conceptual Authoring, is targeted at question-answering systems where reliability and transparency are critical, and where users cannot be expected to undergo extensive training in question composition. This scenario is found in most corporate domains, especially in applications that are risk-averse. We present a proof-of-concept system we have developed: a question-answering interface to a large repository of medical histories in the area of cancer. We show that the method allows users to successfully and reliably compose complex queries with minimal training.

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