Measure the search engine performance

We can regard Web information search as an Information Retrieval problem, that is, a document composed of web pages can retrieve documents related to user queries in a centralized manner. therefore, we can use the recall and precision parameters of traditional information retrieval systems to measure the performance of a search engine.

The full query rate is the ratio of the number of retrieved documents and the number of all relevant documents in the document set. It measures the full query rate of the retrieval system (search engine;

Precision is the ratio of the number of retrieved documents to the total number of retrieved documents. The most important difference is the accuracy of the retrieval system (the control engine.

The recall and recall rates cannot be the same: When the recall rate is high. low precision; low recall when the precision is high. therefore, we often use the average precision (that is, the average precision of 11 points) of the 11 types of recall to measure the precision of a retrieval system. for the search engine system, because a query always returns a lot of information. therefore, the full query rate is generally not a problem. no search engine system can collect all the same page of the web. The query rate is difficult to compare. Therefore, when evaluating the performance of the search engine. the full query rate is rarely used. currently, search engine systems are very concerned about precision. whether high-relevance and high-quality navigation information is provided for users.

Other indicators of the search engine system include response time, support for peak query, ease of use, and effectiveness of returned results (whether it is a dead chain or outdated information.

There are many factors that affect the performance of a search engine system. the most important thing is the information collection policy and retrieval model, including the update frequency and policy of the index database, the representation of documents and queries, and the matching policy of the evaluation document and user query relevance, the sorting method of query results and the mechanism of user-related feedback.