Improving Search and Information Credibility Analysis from Interaction between Web1.0 and Web2.0 Content

We describe a new concept for improving Web search performance and/or increasing the information credibility of search results using Web1.0 and Web2.0 content in a complementary manner. Conventional Web search engines still suffer from a low precision/recall ratio, especially for searching multimedia content (images, videos etc.). The quality control of Web search is generally insufficient due to low publishing barriers. As a result, there is a large amount of mistaken and unreliable information on the Web that can have detrimental effects on users. This calls for technology that facilitates the judging of the trustworthiness or credibility of content and the accuracy of the information that users encounter on the Web. Such technology should be able to handle a wide range of tasks: extracting credible information related to a given topic, organizing this information, detecting its provenance, and clarifying background, facts, and other related opinions and their distribution. We propose and describe a concept of enhancing the search performance of conventional Web search engines and analyzing information credibility of Web information using the interaction between Web1.0 and Web2.0 content. We also overview our recent research activities on Web search and information credibility based