Search Engine
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seminar surveyer
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#1
27-10-2010, 01:17 PM



Prepared by:
Mohini G. Gonawala


.ppt   searchengine.ppt (Size: 3.41 MB / Downloads: 167)


Introduction

A program that searches documents for specified keywords and returns a list of the documents where the keywords were found.
The search results are generally presented in a list of results and are often called hits. The information may consist of web pages, images, information and other types of files.

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project report helper
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#2
02-11-2010, 06:01 PM


.ppt   SEO.ppt (Size: 468 KB / Downloads: 93)


.doc   SEO Report.doc (Size: 56.5 KB / Downloads: 82)

Search Engine Optimization


INTRODUCTION


Webmasters and content providers began optimizing sites for search engines in the mid-1990s, as the first search engines were cataloging the early Web. Initially, all a webmaster needed to do was submit a page, or URL, to the various engines which would send a spider to "crawl" that page, extract links to other pages from it, and return information found on the page to be indexed. The process involves a search engine spider downloading a page and storing it on the search engine's own server, where a second program, known as an indexer, extracts various information about the page, such as the words it contains and where these are located, as well as any weight for specific words and all links the page contains, which are then placed into a scheduler for crawling at a later date. Site owners started to recognize the value of having their sites highly ranked and visible in search engine results. According to industry analyst Danny Sullivan, the earliest known use of phrase "search engine optimization" was a spam message posted on Usenet on July 26, 1997. Early versions of search algorithms relied on webmaster-provided information such as the keyword meta tag, or index files in engines like ALIWEB. Meta-tags provided a guide to each page's content. But using meta data to index pages was found to be less than reliable because the webmaster's account of keywords in the meta tag were not truly relevant to the site's actual keywords. Inaccurate, incomplete, and inconsistent data in meta tags caused pages to rank for irrelevant searches.Web content providers also manipulated a number of attributes within the HTML source of a page in an attempt to rank well in search engines. Page and Brin founded Google in 1998. Google attracted a loyal following among the growing number of Internet users, who liked its simple design. Off-page factors such as PageRank and hyperlink analysis were considered, as well as on-page factors, to enable Google to avoid the kind of manipulation seen in search engines that only considered on-page factors for their rankings. Although PageRank was more difficult to game, webmasters had already developed link building tools and schemes to influence the Inktomi search engine, and


these methods proved similarly applicable to gaining PageRank. Many sites focused on exchanging, buying, and selling links, often on a massive scale. Some of these schemes,
or link farms, involved the creation of thousands of sites for the sole purpose of linkspamming. To reduce the impact of link schemes, as of 2007, search engines consider a wide range of undisclosed factors for their ranking algorithms. Google says it ranks sites using more than 200 different signals. The three leading search engines, Google, Yahoo and Microsoft’s Live Search, do not disclose the algorithms they use to rank pages.
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#3
29-12-2010, 03:17 PM




Submitted By:
Anatoli Uchitel
Tommer Leyvnad

Purpose & Preface
This document describes our final work in the course “Web IR techniques”. We’ve implemented a Search Engine (SE) with re-ranking that uses both stemming and stop-words.
This document first describes the algorithms that we’ve used along with the data-structures it operates on. We then explain the high-level design of our search engine. The appendixes contain rather technical data for compiling, running etc.
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#4
29-12-2010, 03:23 PM




Final assignment for course: Web based IR techniques/TAU 2001

[color=#FF1493]
Submitted By:
Anatoli Uchitel
Tommer Leyvnad

Purpose & Preface
This document describes our final work in the course “Web IR techniques”. We’ve implemented a Search Engine (SE) with re-ranking that uses both stemming and stop-words.
This document first describes the algorithms that we’ve used along with the data-structures it operates on. We then explain the high-level design of our search engine. The appendixes contain rather technical data for compiling, running etc.
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