实现用户兴趣模型的更新控制。
用户兴趣模型是智能搜索引擎系统中的重要组成部分。
User interest profile is one of the important components of intelligent search engine.
用户兴趣模型的建立和更新是实现智能化搜索的核心。
Creating and updating the user interest model are the key technology of intelligent search.
实验证明，建立用户兴趣模型的方法是合理和有效的。
Experiments results prove that the researching method of building user interest model is reason-able and effective.
一个层次结构用户兴趣模型是一个以单个兴趣向量为节点的树。
A hierarchical user interest model is a tree whose nodes are the single interest vectors.
信息过滤中用户兴趣模型的表示是影响过滤精确度的最重要的因素之一。
The representation of user profile is one of most important factors influencing the precision of information filtering.
用户兴趣模型的表示是信息过滤中的关键技术，它直接关系到过滤效果的好坏。
The representation of user profile plays an important role in the information filtering, and decides whether filtering will be successful.
在系统运行初期，由用户指定邮件的类别，系统根据用户的分类建立用户兴趣模型。
In the initial stage of system, user appoints the classification of every mail and system set up a user model according to the classification.
为了对用户提供更优质的推荐，基于用户兴趣模型的推荐系统的效率显得尤为重要。
The efficiency of recommendation system which is based on user interest model is particularly important for the goal of better quality of the recommendation.
而用户兴趣模型正是用户和兴趣的信息模型，用户兴趣模型直接影响到个性化的信息服务。
Model and the user is interested in the interest of users and the information model, the user interested in a direct impact on the model of personalized information services.
同时，系统能根据用户兴趣模型判断返回结果和用户兴趣的匹配程度，并且实现全文提供功能。
Moreover, the system can measure the match between returned results and user interests based on the user model, and achieve full text supply function.
本论文详细分析了个性化搜索技术涉及到的各种模型，包括用户兴趣模型、传统过滤模型和搜索模型。
This thesis is to describe many models involved in the personalized search, including user interest model, classic filtering model and search model.
因此，如何建立高质量的用户兴趣模型，并将其应用于查询结果的优化，是一项具有实际应用价值的研究课题。
Therefore, how to establish high quality user interest model, and use it to optimize the query results is a research subject with practical application value.
论文的第四章经过用户兴趣模型设计、系统分析、系统设计等环节，构建了农业信息智能推送系统，并进行了系统初步实现。
The fourth chapter firstly focuses on system analysis, system design and so on, and then constructs and implements the agriculture information intelligent push sytem.
研究了从HTML编写的网页映射到XML文档的过程，并从中提取符合用户兴趣模型的UCL字段，从而达到网页自动标引的目的。
In order to achieve the computer automatic indexing, we study the mapping process from HTML to XML , and extract the UCL information of fitting for the interesting profile of client users.
该方法通过设计一种客户端的用户兴趣挖掘模型，同时将用户兴趣模型与局部上下文分析方法相结合，克服了局部上下文分析的缺陷。
By mining the user profile in client computer, then combining user profile and traditional LCA, the method could resolve the defect of LCA.
本文在综合兴趣模型研究现状的基础上，结合微博数据集对微博用户的特征进行分析，建立微博用户兴趣模型，并提出基于微博用户兴趣模型的发现算法。
Based on the research of user interest model, the feature of weibo user will be analyzed according to the weibo data collection, detection algorithm of weibo user interest model will be proposed.
Eclipse许可模型将允许用户在平台中构建所需的任意内容并重新将它发布为惟一的发行版(如果对此感兴趣，请参阅eclipse PublicLicense获得详细信息)。
The Eclipse licensing model allows users to build whatever they want on the platform and re-release it as a unique distribution. (If this interests you, see the Eclipse Public License for details.)
根据用户的访问历史，利用知网建立基于概念关系的用户兴趣森林模型。
According to the users navigation history and the concept relations living in the HowNet, a user interest forest model based on the relative relations of concepts is constructed.
个性化服务系统首先需要建立用户模型，然后才能针对不同用户的不同兴趣偏好提供个性化服务。
Before the personalized services for different users with different interests and preferences are provided, user models for the personalized service system must be constructed.
兴趣模型是个性化信息技术中的关键问题，有效地获取用户兴趣信息，能更好地为网络用户提供信息服务。
User's interest model is the key in personal information technology and can provide information service for net user to obtain user's interest.
基于马尔科夫模型的浏览路径预测，仅仅从用户的浏览会话本身出发来预测用户下一步的链接，并不能捕获用户的真正兴趣所在。
Research prediction of based on Latent Markov model, only from to research conversation itself set out to predict user's next chaining user, can not catch users' real interest.
在对第二代搜索引擎分析的基础上，运用向量空间模型，设计并实现了一个完整的可学习用户兴趣并可动态调整的个性化搜索引擎。
The 2nd generation of search engine is analyzed and then a personalized search engine based on SVM(vector space model) that can dynamically learn the interests of users is implemented.
针对用户兴趣和偏好建立用户模型，是整个数字图书馆个性化服务系统中的关键技术。
The establishment of user model, based on the user's interests and hobby, is the key techniques in the individuation-service-system in digital library.
建立了以用户对产品性能的兴趣取向为输入的配置模型。
A model with the input based on the Interest orientation was proposed.
同时本文还研究、构建了基于专业兴趣度的用户知识模型，为用户提供个性化服务，提高系统的智能性。
Meanwhile a user's knowledge model which is found on one's interest in special domain is constructed to provide personal services and improve the accuracy rate of web searching.
分别构建文档特征向量和用户兴趣向量，运用向量空间模型对其做相关性计算，返回用户感兴趣的检索结果。
We set up document feature vectors and user interest vector, and do their correlation calculation by using vector space model, finally return the interested results for the user.
在此基础上，结合用户的个人兴趣，给出了文本特征抽取机制、文本推荐机制、文本与信息需求模型的匹配机制。
Also put forward are the approach for text feature extraction, the pattern of user annotations, and the mechanism for matching texts and profiles.
因此，如何通过分析用户的兴趣偏好建立用户模型，从而来向用户提供良好的个性化服务成为研究的热点课题。
Therefore, how to build user model by analyzing users' interests and preferences, and provide users with excellent personalized service is becoming the hot research topic.
短期兴趣模型则反映了博客用户最近一段时间的兴趣和关注点，若用户持续关注某个兴趣类，则该兴趣类将转化为用户的长期兴趣。
And the short interest model records the blogger's recent interests. If the blogger CARES about something continuously in a period of time, it will be added into the long interest model.
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