Research of Personalized Information Recommendation Theory Model Based Web 3.0

Abstract:

In Web 3.0 times, Internet and Electronic Commerce develop rapidly, it is necessary to solve the problem which is how to recommend the personalized information to the user when the user faces numerous of information. But now, it is only studied from three aspects: collaborative filtering, content analysis, associated rules, which belong to the two sides based on the user and the goods. All of them dig the information from the individual records of history, or the user who similar to the record of history. After analyzing the content of web 3.0, this paper point out how to mining information from the perspective of semantic-formal concept analysis based on the user, and then draw the personalized information recommendation model. After analyzing the user’s information behavior, we can find the the user’s preferences, finally recommend the proper information about commodity to the user and improve the user's satisfaction.

• Periodical: Advanced Materials Research (Volume 679)
• Pages: 137-142
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.679.137
• Online since: April 2013
• Authors: Hui Juan Wu, Bao Xiang Xu, Qing Song Tang
• Keywords: Electronic Commerce, Formal Concept Analysis (FCA), Personalized Information Recommendation, Web3.0

References

[1] Web3. 0 is about Intelligence [EB/OL]. [2008-01- 10]. http: /bub. blicio. us/?p=432.

[2] Chenhui Tan, and Qingyan Liu, The Open API appear, the origin and the status quo, Programmer, vol. 07, pp.38-41, (2008).

[3] Huixiang Xiong, and Shan Chen, and Yingying Xu, Web 3. 0-based personalized information aggregation technology research, Intelligence theory and practice, vol. 8, pp.95-99, (2011).

[4] Hanhua Wu, and Zizhou Wang, From the Web 3. 0" to "Library 3. 0, Library Construction, vol. 4, pp.66-70, (2008).

[5] Huixiang Xiong, and Xuedong Wang, Category Focus Research Face Web 3. 0, Library and Information Service, vol. 3, pp.104-105, (2010).

[6] Dingquan Chen, and Libin Wu. Social Network recommendation, Journal of Information, vol. 11, pp.37-42, (2007).

[7] Jiming Hu, Social Recommendation Service Review, Information Science, vol. 2, pp.308-309, (2011).

[8] Walter F. E, A model of a trust-based recommendation system on a social network, Autonomous Agents and MultiAgent Systems, vol. 1, pp.57-74, (2008).

[9] Li Y. M., et al. A synthetical approach for blog Recommendation: Combining trust, social relation, and semantic analysis, Expert Systems with Applications, vol. 3, pp.6536-6547, (2009).

DOI: 10.1016/j.eswa.2008.07.077

[10] Hongsheng Xu, and Xiajiong Shen, and Zongtian Liu, Based on the form of the concept of the Semantic Web ontology building and Prospects, Computer Science, vol. 2, pp.171-174, (2007).