Applying Short-term Memory to Social Search Agents

This paper presents about our research in social search. Generally, the research in social search falls into two principal challenges. The first challenge is how to find more relevant answers to the question. The second one is how to increase speed in finding relevant answers. Recently, we had provi...

Full description

Saved in:
Bibliographic Details
Published in:Procedia computer science 2015, Vol.68, p.217-226
Main Authors: Mansilla, Albert Trias i, Sethserey, Sam, Esteva, Josep Lluís de la Rosa i
Format: Article
Language:English
Subjects:
Asknext
BFS
LRU Cache
Multiagent systems
query routing
Question Waves
Sistemes multiagent
Social networks
Social search
Xarxes socials
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper presents about our research in social search. Generally, the research in social search falls into two principal challenges. The first challenge is how to find more relevant answers to the question. The second one is how to increase speed in finding relevant answers. Recently, we had provided two algorithms called Asknext and Question Waves to find more relevant answers compared to the baseline algorithm BFS. But, the search speed of the two proposed algorithms still the subject to improve. In this paper, we introduce the agents’ ability of learning the answers from the interactions with other agents so that they can quickly answer the question of other agents. We model this learning process by implementing the concept of data caching as the short-term memory of each social search agent. The result improvement of the speediness and the reduction of the number of messages used to communicate between agents, after apply agent's short-term memory concept, demonstrates the usefulness of the proposed approach.
ISSN:1877-0509
1877-0509
DOI:10.1016/j.procs.2015.09.237