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  2. Theses and Dissertations
  3. ASU Electronic Theses and Dissertations
  4. Decentralized information search
  5. Full metadata

Decentralized information search

Full metadata

Description

Our research focuses on finding answers through decentralized search, for complex, imprecise queries (such as "Which is the best hair salon nearby?") in situations where there is a spatiotemporal constraint (say answer needs to be found within 15 minutes) associated with the query. In general, human networks are good in answering imprecise queries. We try to use the social network of a person to answer his query. Our research aims at designing a framework that exploits the user's social network in order to maximize the answers for a given query. Exploiting an user's social network has several challenges. The major challenge is that the user's immediate social circle may not possess the answer for the given query, and hence the framework designed needs to carry out the query diffusion process across the network. The next challenge involves in finding the right set of seeds to pass the query to in the user's social circle. One other challenge is to incentivize people in the social network to respond to the query and thereby maximize the quality and quantity of replies. Our proposed framework is a mobile application where an individual can either respond to the query or forward it to his friends. We simulated the query diffusion process in three types of graphs: Small World, Random and Preferential Attachment. Given a type of network and a particular query, we carried out the query diffusion by selecting seeds based on attributes of the seed. The main attributes are Topic relevance, Replying or Forwarding probability and Time to Respond. We found that there is a considerable increase in the number of replies attained, even without saturating the user's network, if we adopt an optimal seed selection process. We found the output of the optimal algorithm to be satisfactory as the number of replies received at the interrogator's end was close to three times the number of neighbors an interrogator has. We addressed the challenge of incentivizing people to respond by associating a particular amount of points for each query asked, and awarding the same to people involved in answering the query. Thus, we aim to design a mobile application based on our proposed framework so that it helps in maximizing the replies for the interrogator's query by diffusing the query across his/her social network.

Date Created
2013
Contributors
  • Swaminathan, Neelakantan (Author)
  • Sundaram, Hari (Thesis advisor)
  • Davulcu, Hasan (Thesis advisor)
  • Turaga, Pavan (Committee member)
  • Arizona State University (Publisher)
Topical Subject
  • Computer Science
  • Querying (Computer science)
  • Database searching
  • Online social networks
Resource Type
Text
Genre
Masters Thesis
Academic theses
Extent
xiii, 67 p. : ill. (some col.)
Language
eng
Copyright Statement
In Copyright
Reuse Permissions
All Rights Reserved
Primary Member of
ASU Electronic Theses and Dissertations
Peer-reviewed
No
Open Access
No
Handle
https://hdl.handle.net/2286/R.I.18767
Statement of Responsibility
by Neelakantan Swaminathan
Description Source
Viewed on Feb. 6, 2014
Level of coding
full
Note
Partial requirement for: M.S., Arizona State University, 2013
Note type
thesis
Includes bibliographical references (p. 66-67)
Note type
bibliography
Field of study: Computer science
System Created
  • 2013-10-08 04:24:25
System Modified
  • 2021-08-30 01:38:16
  •     
  • 1 year 5 months ago
Additional Formats
  • OAI Dublin Core
  • MODS XML

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