Indexing and retrieval for the Web

Restricted inflectional form generation in management of morphological keyword variation

“…Nevertheless the findings of this paper should be tested further with more languages and in different query environments to make sounder conclusions about the proposed method' s applicability in IR Applications include in particular Web IR in languages poor in morphological resources (sometimes called "low density languages"). Also the multilinguality of a web index (Rasmussen 2003) can be dealt with the approach. …”

Information retrieval on the web

“…Two of the most recent are the ARIST chapters by Rasmussen (2003) on indexing and retrieval from the Web, which reviews research on indexing and ranking functions of search engines on the Web, and Bar-Ilan's (2004) on the use of Web search engines in information science research, which examines research into the design and use of search engines from both social and application-centered perspectives.…”

The use of web search engines in information science research

“…Currently, the best‐known search engine of this kind is Google. A crawler‐based, or automatic, search engine is made up of three major parts: the crawler, the indexer, and the query engine (for further details, see, for example, Arasu, Cho, Garcia‐Molina, Paepcke, & Raghavan, 2001; Brin & Page, 1998; or Rasmussen, 2003).…”

“…Several previous ARIST chapters have discussed the Internet and information science. Among these are (in chronological order): Wilson's (1999) review of informetrics, Molyneux and Williams (1999) on measuring the Internet, Borgman and Furner (2002) on scholarly communication and bibliometrics, Herring (2002) on computer‐mediated communication on the Internet, data mining by Benoǐt (2002), and Rasmussen (2003) on indexing and retrieval for the Web.…”

“…A large number of studies have evaluated search engine performance. Early studies are reviewed extensively by Rasmussen (2003) and Oppenheim et al (2000). Precision (the percentage of retrieved documents that are “relevant”) and recall (the percentage of all “relevant” documents in the database that are retrieved) are the two major measures used to evaluate information retrieval systems.…”