The Research And Application Of Information Retrieval Technology Based On CSCW

With the increasing of Internet resouces, it becomes more and more difficult for people to obtain the information they needed, and this cause the phenomenon of "getting lost in information" and "information overload". People urgently need high-performance information retrieval technology (IRT) to meet the growing demand for information, that results in the rapid development of the IRT and make it become one of the research hot spots.Very many factors can affect the performance of an information retrieval system (IRS), and the most important is the information retrieval model. How to unify with user relevant feedback technology to improve the performance of an IRS has been the research topic of many scholars, and its main thought is the highly effective information retrieval surely relies on the correct user feedback. But depending on the single user to get the correct feedback has a lot of limitation to the improvement of performance, while using the multi-user collaborative work method to get the cerrect feedback is more reasonable, and it is easier to construct good query expression to improve the performance.The paper firstly analyzed the present researching status of the IRT, discussed three essential factors and key technologies of CSCW, and researched three classic information retrieval models, user relevance feedback technology and result merging algorithms. Secondly, aiming at existing problems of IR, such as low accuracy, low rates of information coverage and bad efficiency etc, combined with CSCW, user relevance feedback technology and meta-search technology, we put forward a collaborative feedback information retrieval model. On this basis, the paper carried on the analysis and the research to the design of collaborative IRS, and discussed the framework of IRS based on the CSCW. This system take message primitive based communication mechanism as the foundation of collaborative work, applies collaborative feedback information retrieval model to the meta search engine, and has realized the multi-user collaborative information retrieval function.Finally, this paper implemented system's core modules, solved some problems related with collaborative feedback and IRT, and confirmed the feasibility and the validity of the model with a view to provide reference and assistance to the research of IRT.