Making the road by searching - A search engine based on Swarm Information Foraging
Clinical Orthopaedics and Related Research(2009)
摘要
Search engines are nowadays one of the most important entry points for
Internet users and a central tool to solve most of their information needs.
Still, there exist a substantial amount of users' searches which obtain
unsatisfactory results. Needless to say, several lines of research aim to
increase the relevancy of the results users retrieve. In this paper the authors
frame this problem within the much broader (and older) one of information
overload. They argue that users' dissatisfaction with search engines is a
currently common manifestation of such a problem, and propose a different angle
from which to tackle with it. As it will be discussed, their approach shares
goals with a current hot research topic (namely, learning to rank for
information retrieval) but, unlike the techniques commonly applied in that
field, their technique cannot be exactly considered machine learning and,
additionally, it can be used to change the search engine's response in
real-time, driven by the users behavior. Their proposal adapts concepts from
Swarm Intelligence (in particular, Ant Algorithms) from an Information Foraging
point of view. It will be shown that the technique is not only feasible, but
also an elegant solution to the stated problem; what's more, it achieves
promising results, both increasing the performance of a major search engine for
informational queries, and substantially reducing the time users require to
answer complex information needs.
更多查看译文
关键词
human computer interaction,real time,information overload,machine learning,user requirements,information need,swarm intelligence,information retrieval,learning to rank,search engine
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要