IR in Community Question-Answering

author: Chirag Shah, School of Communication and Information, Rutgers, The State University of New Jersey
published: Oct. 8, 2013,   recorded: August 2012,   views: 2386
Categories

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.
  Delicious Bibliography

 Watch videos:   (click on thumbnail to launch)

Watch Part 1
Part 1 53:07
!NOW PLAYING
Watch Part 2
Part 2 1:29:59
!NOW PLAYING
Watch Part 3
Part 3 1:23:27
!NOW PLAYING
Watch Part 4
Part 4 1:13:34
!NOW PLAYING

Description

This course will introduce the students to various challenges and opportunities in rapidly growing community-based question-answering (CQA), with emphasis on content quality and ranking, as well as usage and user satisfaction. Question answering helps one go beyond traditional keywords-based querying and retrieve information in more precise form than given by a document or a list of documents. Several CQA services have emerged in the recent years allowing information seekers pose their information need as questions and receive answers from their fellow users. This has created new challenges for IR researchers relating to content ranking and evaluation within and outside a CQA site. The social/community aspect of IR is unique and important to address in the swiftly changing landscape of the Web.The course will cover (1) understanding structures and functionalities of a CQA service from a developer's view, (2) criteria relating to motivations and satisfaction from a user's view, and (3) methodology for collecting and analyzing CQA data from a researcher's view. In particular, the course will teach a student tools and techniques for obtaining data from various CQA sites, extracting textual and non-textual features from this content, and using them to rank and evaluate for its usefulness and relevance.

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Write your own review or comment:

make sure you have javascript enabled or clear this field: