Keyword search in the Deep Web

The Deep Web is constituted by data accessible through Web pages, but not readily indexable by search engines, as they are returned in dynamic pages. In this paper we propose a framework for accessing Deep Web sources, represented as relational tables with so-called ac- cess limitations, with keyword-based queries. We formalize the notion of optimal answer and investigate methods for query processing. To our knowledge, this problem has never been studied in a systematic way

Processing keyword queries under access limitations

The Deep Web is constituted by data accessible through Web pages, but not readily indexable by search engines, as they are returned in dynamic pages. In this paper we propose a framework for accessing Deep Web sources, represented as relational tables with so-called access limitations, with keyword-based queries. We formalize the notion of optimal answer and propose methods for query processing. To the best of our knowledge, ours is the first systematic approach to keyword search in such context

Using Google Keyword Statistics to Explain Changes in Traffic to Internet Sites Related to Global Environmental Management

Google recently provided a keyword statistics tool to support its “AdWords” program that conducts a deep evaluation of individual web sites. It provides detailed information on the keywords in the site and an index of monthly and average statistics for these keywords over the past year for users of the Google search engine. The data is intended to help with the design of internet sites and to support bidding for keywords that when purchased become AdWords that draw traffic through the sponsored links of Google search. This paper describes an analysis of the traffic, keywords, and search rank results for a sample of internet sites related to global environmental management for March 2007 and March 2008. Surprisingly, the analysis shows absolutely no correlation between changes in traffic and changes in keyword statistics. There is only weak evidence that the Google search rank affects traffic. One interesting result was that highly trafficked sites received less traffic while less trafficked sites received more traffic, a regression to mean traffic

Comparing the Performance of Information Retrieval of Semantic and Keyword Search Engines Based on Phrase Search

Purpose: The aim of the research is to compare the performance of Information Retrieval of semantic and keyword search engines based on phrase search (simple & complex). Methodology: The present applied and semi-experimental research community includes all active search engines on the web. Research samples were selected based on stratified random sampling and purposive sampling. The data collection tool of two researcher-made checklists includes ten simple and complex phrase queries. Findings: Bing and Cluuz (with similar precision of 53%), DuckDuckGo, and Yahoo were the most accurate in searching for simple phrases, respectively. Bing, DuckDuckGo, Yahoo, and Cluuz were the most accurate in their search for complex terms, respectively. In general, Bing, DuckDuckGo, Cluuz and Yahoo have the highest precision, respectively. Also, the average total precision of keyword search engines is more heightened than semantic search engines. Conclusion: The Bing keyword search engine performs better than the other three semantic search engines and other keywords. Semantic search engines claim to have more capabilities in retrieving relevant information than keyword search engines. But in this study, it was found that Cluuz and DuckDuckGo do not excel in search terms over keyword search engines. These tools did not perform as well as semantic web search engines, and it seems that they have a long way to go to become real semantic search engines. And to achieve this, it is necessary to use the facilities, tools, modules, and emerging technologies of the new age, such as machine learning, deep learning, combining these modules with pervasive techniques, data mining, etc. Value: So far, not been compared the phrase search performance in the sample semantic and keyword search engines. And in this regard, the researcher has tried to achieve an actual result with an exact Survey

Distributed Information Retrieval using Keyword Auctions

This report motivates the need for large-scale distributed approaches to information retrieval, and proposes solutions based on keyword auctions