|Title:||The implementation of personalized information retrieval in Web-based financial news digest system|
|Subject:||Hong Kong Polytechnic University -- Dissertations.|
Journalism, Commercial -- Data processing.
Web search engines.
World Wide Web -- Subject access.
|Department:||Department of Computing|
|Pages:||x, 102 leaves : ill. ; 30 cm.|
|Abstract:||In the survey report "The 22nd Statistical Survey Report on the Internet Development in China" Internet News is the second in the top 10 of the Internet application. A large growing number of Internet users, more and more people pay attention to financial news. People try to reduce the information asymmetric through the Internet. In the area of finance, information is increasing rapidly. The financial news digest system is one kind of financial system; it can provide the effective support and the help for the user. It is quite difficult for Internet users and the majority of financial researchers to accurately obtain financial information on the Internet manually. Especially for financial professionals, we need a professional information retrieval tool to obtain the necessary professional information. But all kinds of Internet finance information as well as more Internet users require custom-made and personalized financial information. It gradually becomes very important in daily application. Nowadays almost all popular free online reader systems just provide a RSS reader service, there is not having a part for the retrieval of ordinary web pages. At the same time there is no system specific to the users who are interested to look at financial news. It is difficult to recommend news by similar of users. In this dissertation, will try to describe how to build an easily and simple system called getlnOne. It only concern with the financial industry, it can support subscription RSS / Atom and the ordinary web pages, find out tags from news and let people modify or confirm. So the system can recommend news through the same tag.|
|Rights:||All rights reserved|
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