The official engine has indexed approximately 80 millions URLs, whereas the new one has indexed more than the double of this. The proportions of unsatisfactory results are about the same for all three search engines.
Besides, new features, such as hyperlinks and metatags are integral parts of the Web documents, and may give rise to better ranking algorithms.
And if you have kids at home with you, you probably get interrupted often. Therefore, researchers publishing works on comparison of Web search engines use precision as their main evaluation measure [Winship95, DingMarch96, ChuRos96, ClaWil97, LeiSri97], evaluating only the highest ranked hits.
Therefore both relevance and resource consumption must be considered when evaluating ranking algorithms.
Besides, they will be asked to evaluate the search engines layout, help features, satisfaction with the responses etc.
Some possible future experiments A Web search engine should deliver adequate documents, and do it fast, but has limited resources. He used the text in the hyperlinks as a representation for the documents that is pointed Evaluation on search engines by the hyperlinks.
One is a comparison between three Web search engines, and the other is a comparison between two sizes of the number of indexed documents in a search engine. A genetic algorithm can give the optimal weight for each of these factors.
The evaluation of Web search engines and the search for better ranking algorithms. I used a three point relevance scale, relevant 1partly relevant 0. In this way, the document is described with the words that others use about it, not with the words that is used in the document itself.
Their conclusion is that in order to achieve this, one should have two runs that are not too similar, and both runs should perform reasonably well. Counting how many times the highest ranked document is deemed relevant for the twelve queries, the probability of getting a relevant document as the first, was estimated to 0.
It is thus time for both Yahoo! A challenge here is to find a method that is feasible for large data volumes. A size experiment In another experiment, I wanted to test whether the number of documents indexed has a significant impact on the precision. In the first section I show the results from two relevance experiments.
Here "significant" hyperlinks to a document enlarged the rating of this document, thereby trying to heighten the precision level. I believe that the results truly reflect the sentiments of users based on their personal information needs and assessments.
However, for the general public, the situation may be reversed. Proceedings of the 59th annual meeting of the American Society for Information Science, Future evaluation should involve people from different walks of life, which of course is more difficult to do.
Researchers like Su [Su93, Su98], Green [Green95] and Borland and Ingwersen [BorIng97] argue that relevance is a complex item with many topical aspects, one of them being who is assigning the relevance, another being which relevance is considered. From the results, the mean precision P 10 of each engine was estimated.
An approximate test based on the X2 statistics, showed no significant differences in these probabilities. The total sum of relevant pages was defined as the sum of the relevant, retrieved documents over all the three engines, counting equal documents found by two or more engines only once.
Another difficulty is that as more and more documents are gathered in the database, it will be impossible to evaluate all of them for relevance. This gave a significant difference in the X2 test, but since the numbers of observations are small, this test is questionable.
The title-only version of the queries were sent to the two engines after adding a plus sign to each word in order to get the AND version rather than the default OR version of the queriesand the top twenty documents were evaluated for relevance.
Ten of the queries were fetched from a similar study made by Clarke and Willet [ClaWil97], the last two were formulated by myself.
That is, relevant documents found by no groups, will not count in the recall computation. Is an observed precision difference of 0. Ng and Kantor [NgKant98] found in their experiments with TREC-4 runs that combining two runs can improve the precision beyond the precision of each of the runs.
More precise evaluation could be done if they were ranked in a non binary fashion, as we want the highly relevant documents at the top of the list of results.Search engines often come packaged with logging and reporting frameworks to help in deciphering this information and identifying trends.
This information can be used to feed and control the search-relevancy algorithm to Search Engine Evaluation based on Relevancy.
On Search Engine Evaluation Metrics Inaugural-Dissertation zur Erlangung des Doktorgrades der Philosophie (Dr. Phil.) The present work deals with certain aspects of the evaluation of web search engines. This does not sound too exciting; but for some people, the author included, it really is a. Free Essay: Final Evaluation As I have come to an end of this Unit 2, I am now going to evaluate on each elements that were useful to me while I was doing.
The contribution of this study is a method for automatic performance evaluation of search engines. In the paper we first introduce the method, automatic Web search engine evaluation method (AWSEEM).
Then we show that it provides statistically significant consistent results compared to human-based evaluations. Personal Evaluations of Search Engines: Google, Yahoo!
and MSN. Bing Liu. Department of Computer Science University of Illinois at Chicago. Comparison of search evaluation results from fall.
The literature of the evaluation of Internet search engines is reviewed. Although there have been many studies, there has been little consistency in the way such studies have been carried out.Download