When experts agree

Author:

Bharat Krishna1,Mihaila George A.1

Affiliation:

1. Compaq, Systems Research Center, Palo Alto, Mountain View, CA

Abstract

In response to a query, a search engine returns a ranked list of documents. If the query is about a popular topic (i.e., it matches many documents), then the returned list is usually too long to view fully. Studies show that users usually look at only the top 10 to 20 results. However, we can exploit the fact that the best targets for popular topics are usually linked to by enthusiasts in the same domain. In this paper, we propose a novel ranking scheme for popular topics that places the most authoritative pages on the query topic at the top of the ranking. Our algorithm operates on a special index of "expert documents." These are a subset of the pages on the WWW identified as directories of links to non-affiliated sources on specific topics. Results are ranked based on the match between the query and relevant descriptive text for hyperlinks on expert pages pointing to a given result page. We present a prototype search engine that implements our ranking scheme and discuss its performance. With a relatively small (2.5 million page) expert index, our algorithm was able to perform comparably on popular queries with the best of the mainstream search engines.

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Science Applications,General Business, Management and Accounting,Information Systems

Cited by 14 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Development of Solar-Powered Vehicle to Clean up the Waste from the Sewage System;Lecture Notes in Mechanical Engineering;2022

2. The Research on Improving Algorithms for Hilltop to Improve Search Quality;Recent Advances in Information and Communication Technology 2016;2016

3. The Research on Webpage Ranking Algorithm Based on Topic-Expert Documents;Advances in Intelligent Systems and Computing;2015

4. Ranking Documents with Query-Topic Sensitivity;2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology;2012-12

5. Architecture for Automated Search and Negotiation in Affiliation among Community Websites and Blogs;Trends in Applied Intelligent Systems;2010

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3