Combining Information from Multiple Internet Sources

application presented in this paper combines the retrieved results using advanced methods.
In this approach application utilizes agents as experts in knowledge extracted from the
results provided by search engines. It uses JADE agent framework to create a multi-agent
environment which aids information retrieval. It is interfaced through a web page when one can
input a query and wait for the result. In the core of the system agents serve as miners of data from
multiple search engines. Simply saying, they possess the knowledge that we are apparently looking
for. So, when we ask several experts the same question we expect that they will provide us with the
best results possible. Would not it be better if they arrived at some agreement about the answer thus
giving us a single combined opinion This thesis aims at answering those questions. It investigates
coherency and performance of each of the three methods used for filtering the answers so that the
filtered result sets are smaller but hopefully more meaningful. Those methods are then compared
with each other; to see which one provides the most promising results.
There are three methods utilized in this work for yielding the final results: Game theory,
Auction and Consensus. In the Game theory approach the process of combining results is compared
to a game in which the game players are agents that decide about the information destination by
either discarding or keeping it. An Auction based approach is almost similar to the “real-life”
auction, but here agents decide about which information can be obtained for the lowest price.
Consensus method uses more centralized approach since it takes the highest-ranked information
from all result sets and checks how common is this result among those obtained from all search
engines. All of those methods are described in the thesis; their implementation and effectiveness are
presented.
While consensus algorithm was already used as a tool for combining information from search
engines [1], two other algorithms: Game theory and Auction were used for a different task - as
methods of negotiation in Agent-based system for classification tasks - the NeurAge system,
described in [7], [8] and [9]. Since Consensus based approach had been used as a way for
combination of information retrieved from multiple Internet sources, there was no need for adapting
the algorithm to our needs - it was used in the same manner as in [1]. Furthermore, in the AGWI
system search engines were selected randomly – there were more search engines than agents
utilizing those. On the other hand, Game theory and Auction required adjusting to deal with data
fundamentally different from what they were dealing with in their original version. Adjustment
details are presented further in the paper; mainly in chapter 3.
1.1 Aim of the thesis
Are the Game theory based, Auction based and Consensus based approaches a good way of
combining the information obtained from multiple Internet sources By creating an application
3