| 1. | Based on some traditional algorithms , this thesis provides a weighted star cluster algorithm to learn user profile
对已有算法进行改进，提出了一种加权的星型聚类算法以学习用户的兴趣特征。 |
| 2. | The profile of cop is fused from the profiles of its members , so the gaining of the user profiles is the base of cop modeling
Cop的兴趣特征是由其成员用户的兴趣特征融合而来，因此用户兴趣特征的获取是cop建模的基础。 |
| 3. | With the user model , computer can acquire , store and restore user ' s fuzzy dynamic interests . the information stored in user model make up the condition of ir and make ir more effective
基于用户模型，计算机中可以表达、存储、复现用户模糊的、变化的兴趣特征，其中存储的用户信息构成了过滤条件，使得信息过滤更有效。 |
| 4. | Based on former information filtering approaches and the i ) - s theory , this thesis gains cop " s profile by model ing the interest of cop , studies and implements the cop orientated information filtering technique
基于已有的信息过滤研究与证据理论，本文对cop的兴趣进行建模，得到cop的兴趣特征，并以此为基础研究和实现了面向cop的信息过滤技术。 |
| 5. | The learning algorithms to build user profile are the hot point in the current researches of information filtering . cluster algorithm integrates the advantages of rocchio and knn . but conventional cluster algorithms cannot embody the different interests of users
用户兴趣特征的学习算法是目前信息过滤研究的热点，聚类算法综合了目前流行的两类算法rochio和knn的优点，但传统的聚类算法不能体现用户对文档的不同兴趣度。 |
| 6. | The group users model contains the interest of individuals and the interest of groups . so the integration eigenvector will certainly result in high precision of individual filtering and high recall of collaborative filtering . there are a few significances
其中，综合用户模型不仅反映该用户的个性化兴趣特征，它还包含该用户所在类的兴趣特征，所以基于综合用户模型的教学资源综合过滤既有个体过滤的查准率高的优点，又有协同过滤的查全率高的优点。 |
| 7. | The search of information automatic collection based on the agent of internet is an agent used by individual or common enterprise . it can learn itself time after time to master the interest of the users and send to user filtered information in this way to realize the intelligentized initiative information service
基于agent的internet信息自动提取的研究是一种面向个人用户和一般企业用户的实用智能化信息获取agent ，它可以通过反复学习，掌握用户的兴趣特征，自主在lnternet上搜索用户感兴趣的信息，并且将找到的信息经过过滤后提供给用户，实现智能化的主动信息服务。 |
| 8. | Li this part , the thesis first profiles semantic features of each document by employing chinese information processing technology in order to change documents into the form which can be operated with the help of mathematical methods . second , the thesis profiles each user ' s information needs by three ways : 1 ) accepting the information provided by the user himself ; 2 ) watching the user ' s retrieval action ; and 3 ) analyzing web server log . in this module , users are also classified into different categories according to their information needs
在用户建模中，系统从三方面获取用户信息需求特征，第一，用户主动地向系统提供需求信息；第二，系统检测用户检索行为，从用户检索词分析其需求；第三，系统通过分析web访问日志，得到用户的兴趣所在及兴趣的变化状况，并进一步利用对用户访问文档内容的分析来追踪其兴趣变化，将用户兴趣同样表示为兴趣特征向量，聚类相似用户。 |
| 9. | During the course of information recommending , the thesis combines content - based filtering with collaborative filtering to find particular information for each user , and it also presents different collaborative filtering strategies . in personalized information retrieval , the thesis takes advantage of the user ' s profile which describes particular user ' s information needs to filter useful information from the retrieval results for particular user and to enhance the accuracy of retrieval
与以往系统不同，系统无需用户直接反馈，而是通过其对文档的访问频度、驻留时间及操作行为等来隐式获取用户的评价信息；同时，系统也利用用户候选兴趣特征向量来记录和累计用户潜在的、非主要的兴趣的变化过程，精度更高。 |
