An Overview of Search Engine Evaluation Strategies
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paper_title: The Anatomy of a Large-Scale Hypertextual Web Search Engine

paper_content:

In this paper, we present Google, a prototype of a large-scale search engine which makes heavy use of the structure present in hypertext. Google is designed to crawl and index the Web efficiently and produce much more satisfying search results than existing systems. The prototype with a full text and hyperlink database of at least 24million pages is available at http://google.stanford.edu/ To engineer a search engine is a challenging task. Search engines index tens to hundreds of millions of web pages involving a comparable number of distinct terms. They answer tens of millions of queries every day. Despite the importance of large-scale search engines on the web, very little academic research has been done on them. Furthermore, due to rapid advance in technology and web proliferation, creating a web search engine today is very different from 3years ago. This paper provides an in-depth description of our large-scale web search engine - the first such detailed public description we know of to date. Apart from the problems of scaling traditional search techniques to data of this magnitude, there are new technical challenges involved with using the additional information present in hypertext to produce better search results. This paper addresses this question of how to build a practical large-scale system which can exploit the additional information present in hypertext. Also we look at the problem of how to effectively deal with uncontrolled hypertext collections, where anyone can publish anything they want.
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paper_title: New measurements for search engine evaluation proposed and tested

paper_content:

A set of measurements is proposed for evaluating Web search engine performance. Some measurement are adapted from the concepts of recall and precision, which are commonly used in evaluating traditional information retrieval systems. Others are newly developed to evaluate search engine stability, an issue unique to Web information retrieval systems. An experiment was conducted to test these new measurements by applying them to a performance comparison of three commercial search engines: Google, AltaVista, and Teoma. Twenty-four subjects ranked four sets of Web pages and their rankings were used as benchmarks against which to compare search engine performance. Results show that the proposed measurements are able to distinguish search engine performance very well.
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paper_title: New measurements for search engine evaluation proposed and tested

paper_content:

A set of measurements is proposed for evaluating Web search engine performance. Some measurement are adapted from the concepts of recall and precision, which are commonly used in evaluating traditional information retrieval systems. Others are newly developed to evaluate search engine stability, an issue unique to Web information retrieval systems. An experiment was conducted to test these new measurements by applying them to a performance comparison of three commercial search engines: Google, AltaVista, and Teoma. Twenty-four subjects ranked four sets of Web pages and their rankings were used as benchmarks against which to compare search engine performance. Results show that the proposed measurements are able to distinguish search engine performance very well.
---
paper_title: New measurements for search engine evaluation proposed and tested

paper_content:

A set of measurements is proposed for evaluating Web search engine performance. Some measurement are adapted from the concepts of recall and precision, which are commonly used in evaluating traditional information retrieval systems. Others are newly developed to evaluate search engine stability, an issue unique to Web information retrieval systems. An experiment was conducted to test these new measurements by applying them to a performance comparison of three commercial search engines: Google, AltaVista, and Teoma. Twenty-four subjects ranked four sets of Web pages and their rankings were used as benchmarks against which to compare search engine performance. Results show that the proposed measurements are able to distinguish search engine performance very well.
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Title: An Overview of Search Engine Evaluation Strategies

Section 1: INTRODUCTION
Description 1: Write an introduction to search engines, their components, and the importance of evaluation in search engine development.

Section 2: EVALUATION PARAMETERS
Description 2: Describe the various criterions used to evaluate the performance of search engines, such as effectiveness, efficiency, coverage evaluation, precision, and quality.

Section 3: Automatic evaluation strategies
Description 3: Discuss various automatic evaluation strategies, highlighting different methodologies and their effectiveness.

Section 4: Survey based evaluation strategies
Description 4: Explain survey-based evaluation strategies and provide examples of studies that utilize user surveys to evaluate search engine performance.

Section 5: Relevance scoring method based evaluation
Description 5: Detail the relevance scoring methods used to evaluate search engines, including comparisons of different search engines based on relevance scoring.

Section 6: Evaluation using judgements of Meta search engine
Description 6: Outline methods that involve meta search engine judgements for evaluating search engines and their effectiveness.

Section 7: CONCLUSION
Description 7: Summarize the various search engine evaluation strategies discussed in the paper and conclude with insights and potential areas for further research.