wedge Reading 02-01:The Web As a Graph
wedge Online Copy
* http://www.informatik.uni-trier.de/~ley/db/conf/pods/KumarRRSTU00.html
wedge Local Copy
* Kumar2000
wedge Reading 02-02:The Anatomy of a Large-Scale Hypertextual Web Search Engine
wedge Commentary from : A. Moffat, J. Zobel, and D. Hawking, “Recommended reading for ir research students,” SIGIR Forum, vol. 39, no. 2, pp. 3–14, 2005.
* Commentary: This paper (and the work it reports) has had more impact on everyday life than any other in the IR area. A major contribution of the paper is the recognition that some relevant search results are greatly more valued by searchers than others. By reflecting this in their evaluation procedures, Brin and Page were able to see the true value of web-specific methods like anchor text. The paper presents a highly efficient, scalable implementation of a
ranking method which now delivers very high quality results to a billion people over billions of pages at about 6,000 queries per second. It also hints at the technology which Google users now take for granted: spam rejection, high speed query-based summaries, source clustering, and context(location)-sensitive search. IR and bibliometrics researchers had done it all (relevance, proximity, link analysis, efficiency, scalability, summarization, evaluation) before 1998 but this paper showed how to make it work on the web. For any non-IR engineer attempting to build a web-based retrieval system from scratch, this must be the first port of call.
wedge Online Copy
* dx.doi.org—S0169-7552(98)00110-X
wedge Local Copy
* Brin1998
wedge Reading 02-03: Chapter 20
wedge Christopher D. Manning, Prabhakar Raghavan and Hinrich Schütze, Introduction to Information Retrieval, Cambridge University Press. 2008.
* Online copy:www-csli.stanford.edu—information-retrieval-book.html
* Local copy: www-csli.stanford.edu—information-retrieval-book.html