Spamdexing 93
External links
To report spamdexed pages
- Found on Google search engine (http:/ / http://www. google. com/ contact/ spamreport. html) results
- Found on Yahoo! search engine (http:/ / help. yahoo. com/ l/ us/ yahoo/ search/ spam_abuse. html) results
Search engine help pages for webmasters
- Google's Webmaster Guidelines page (http:/ / http://www. google. com/ support/ webmasters/ bin/ answer.
py?answer=35769) - Yahoo!'s Search Engine Indexing page (http:/ / help. yahoo. com/ help/ us/ ysearch/ indexing/ index. html)
Other tools and information for webmasters
- AIRWeb series of workshops on Adversarial Information Retrieval on the Web (http:/ / airweb. cse. lehigh. edu/ )
- Popular Black Hat SEO Techniques (http:/ / sitemonetized. com/ Top-Black-Hat-SEO-Techniques/ )
- CMMS (http:/ / winmain. vn)
Index
Search engine indexing collects, parses, and stores data to facilitate fast and accurate information retrieval. Index
design incorporates interdisciplinary concepts from linguistics, cognitive psychology, mathematics, informatics,
physics, and computer science. An alternate name for the process in the context of search engines designed to find
web pages on the Internet is web indexing.
Popular engines focus on the full-text indexing of online, natural language documents.[1] Media types such as video
and audio[2] and graphics[3][4] are also searchable.
Meta search engines reuse the indices of other services and do not store a local index, whereas cache-based search
engines permanently store the index along with the corpus. Unlike full-text indices, partial-text services restrict the
depth indexed to reduce index size. Larger services typically perform indexing at a predetermined time interval due
to the required time and processing costs, while agent-based search engines index in real time.Indexing
The purpose of storing an index is to optimize speed and performance in finding relevant documents for a search
query. Without an index, the search engine would scan every document in the corpus, which would require
considerable time and computing power. For example, while an index of 10,000 documents can be queried within
milliseconds, a sequential scan of every word in 10,000 large documents could take hours. The additional computer
storage required to store the index, as well as the considerable increase in the time required for an update to take
place, are traded off for the time saved during information retrieval.