基于本体的个性化信息检索技术研究

针对传统的采用关键词的信息检索方式在个性化方面的不足,提出了一种根据领域本体的个性化信息检索模型.首先获取用户的特征信息,接着利用用户的特征信息构建基于本体的用户兴趣模型,在检索过程中通过领域本体概念和用户兴趣模型对检索请求进行分析并对其进行扩展,获得符合检索意图的结果,在此基础上按兴趣度大小处理后将最终个性化信息检索结果反馈给用户.通过搭建关于本体的个性化检索原型系统,仿真结果验证了改进模型的有效性.     

基于特征映射的互联网频繁模式识别算法

提出了一种基于特征映射的互联网频繁模式识别算法,采用特征映射与聚类相结合的方法,解决了SPADE算法不能反映类信息的问题与大量数据聚类时的效率低下,同时,提出了比较合理的频繁模式定量评价体系,从而完成了识别系统的整体设计,对于处理互联网海量用户数据有着相当重要的作用,同时,可以根据此算法提供个性化推荐等服务来提升用户体验.     

Personalized method for self-management of trunk postural ergonomic hazards in construction rebar ironwork

Construction rebar workers face postural ergonomic hazards that can lead to work-related Lower Back Disorders (LBDs), primarily due to their prolonged awkward working postures required by the job. In a previous study, Wearable Inertial Measurement Units (WIMUs)-based Personal Protective Equipment (PPE) was developed to alert workers when their trunk inclination holding time exceeded acceptable thresholds as defined in ISO standard 11226:2000. However, subsequent field testing identified PPE was ineffective for some workers because the adopted ISO thresholds were not personalized and did not consider differences in individual’s response to postural ergonomic hazards. To address this problem, this paper introduces a worker-centric method to assist in the self-management of work-related ergonomic hazards, based on data-driven personalized healthcare intervention. Firstly, personalized information is gathered by providing each rebar ironworker a WIMU-based personalized mobile health (mHealth) system to capture their trunk inclination angle and holding time data. Then, the captured individual trunk inclination holding times are analyzed by a Gaussian-like probability density function, where abnormal holding time thresholds can be generated and updated in response to incoming trunk inclination records of an individual during work time. These abnormal holding time thresholds are then adapted to be used as personalized trunk inclination holding time recommendations for an individual worker to self-manage their working postures, based on their own trunk inclination records. The proposed worker-centric method to assist in the self-management of ergonomic postural hazards leading to LBDs was field tested on a construction site over a three-month duration. The results of the paired t-tests indicate that posture scores evaluated by the Ovako Working Posture Analysis System (OWAS) significantly decrease when the personalized recommendation is applied, while increase again when the personalized recommendation is removed. Based on data-driven personalized healthcare intervention, the results demonstrate the significant potential of the proposed worker-centric self-management method for rebar workers in preventing and controlling postural ergonomic hazards during construction rebar ironwork.     

A time-aware query-focused summarization of an evolving microblogging stream via sentence extraction

With the number of social media users ramping up, microblogs are generated and shared at record levels. The high momentum and large volumes of short texts bring redundancies and noises, in which the users and analysts often find it problematic to elicit useful information of interest. In this paper, we study a query-focused summarization as a solution to address this issue and propose a novel summarization framework to generate personalized online summaries and historical summaries of arbitrary time durations. Our framework can deal with dynamic, perpetual, and large-scale microblogging streams. Specifically, we propose an online microblogging stream clustering algorithm to cluster microblogs and maintain distilled statistics called Microblog Cluster Vectors (MCV). Then we develop a ranking method to extract the most representative sentences relative to the query from the MCVs and generate a query-focused summary of arbitrary time durations. Our experiments on large-scale real microblogs demonstrate the efficiency and effectiveness of our approach.     

新闻大数据服务平台的设计和实现

浙江广电新闻大数据服务平台依托浙江广播电视集团中国蓝云资源,从新闻数据采集、分析、生产、展现到处置全流程化,是具有广电特色的浙江省内最权威的新闻大数据系统。系统主要用于为节目生产提供互联网新闻线索,同时对台内新闻在互联网的传播效果进行实时反馈,包括文章的传播路径和文章的传播力、影响力计算、综合考评等。同时,基于多租户的设计原则,该平台与中国蓝云平台认证体系对接,可实现租户与用户同步,满足浙江省、市、县三级广电的个性化新闻业务需求。     

基于用户偏好特征挖掘的个性化推荐算法

为了提升社交网络个性化推荐能力,结合用户行为分布进行个性化推荐设计,文中提出基于用户行为特征挖掘的个性化推荐算法,构建社交网络的用户行为信息特征挖掘模型,采用显著数据分块检测方法对社交网络用户特征的行为信息进行融合处理,提取反映用户偏好的语义信息特征量。从情感、关键词和结构等方面根据用户行为特征组,结合模糊信息感知方法进行社交网络个性化推荐过程中的信息融合处理,在关联规则约束控制下,构建社交网络用户偏好特征的混合推荐模型,实现用户偏好特征挖掘,根据语义分布和用户的行为偏好实现社交网络的个性化信息推荐。仿真结果表明,采用所提方法进行社交网络个性化推荐的特征分辨能力较好,对用户行为特征的准确识别能力较强,提高了社交网络推荐输出的准确性。     

Personalised Product Recommendation Model Based on User Interest

The scale of e-commerce systems is increasing and more and more products are being offered online. However, users must find their own desired products among a large amount of unrelated information, which makes it increasingly difficult for them to make a purchase. In order to solve this problem of information overload, and effectively assist e-commerce users to shop easily and conveniently, an e-commerce personalized recommendation system technology has been proposed. This paper introduces the design and implementation of a personalized product recommendation model based on user interest. The “shopping basket analysis” functional model centered on the Apriori algorithm uses the sales data in the transaction database to mine various interesting links between the products purchased by the customers. Moreover, it helps merchants to formulate marketing strategies, reasonably arranges shelf-guided sales, and attracts more customers. This platform adopts a B/S structure and uses JSP+AJAX technology to achieve the dynamic loading of pages. In the background, the Struts2 framework is combined with the SQL Server database to establish the system function module, and then the function is gradually improved according to the requirement analysis, and the development of the platform is finally completed.     

用户非对称信任关系的推荐算法

数据稀疏性是目前协同过滤面临的主要挑战之一。用户间的信任关系为推荐系统提供了有用的附加信息。已有工作主要采用直接信任关系作为附加信息,对间接信任关系考虑得较少。针对这一情况,提出一种融合直接和间接的用户非对称信任关系的推荐算法(ATRec)。首先,构建一种信任传递机制,并利用该机制获得用户间的间接非对称信任关系。其次,根据直接和间接非对称信任关系获得每个用户的信任集合。最后,利用信任集合、最近邻的评分和好评阈值计算出商品的受欢迎程度,进而获得对用户的top-N推荐列表。在真实数据集上的实验结果表明,该算法比主流的推荐算法在top-N推荐性能上有更好的表现。     

The need to achieve: Players' perceptions and uses of extrinsic meta-game reward systems for video game consoles

Microsoft's Xbox and Sony's PlayStation overlay achievement and trophy systems onto their video games. Though these meta-game reward systems are growing in popularity, little research has examined whether players notice, use, or seek out these systems. In this study, game players participated in focus groups to discuss the advantages and disadvantages of meta-game reward systems. Participants described the value of meta-game reward systems in promoting different ways to play games, giving positive feedback about game play, and boosting self-esteem and online and offline social status. Participants discussed completionists, or gamers that want to earn all of the badges associated with the meta-game. Though self-determination theory and its subtheory cognitive evaluation theory suggest that extrinsic rewards might harm players' intrinsic motivation, our findings suggest players may see these systems as intrinsically motivating in this context. The implications of rewards systems for motivation, video game habits, and internet gaming disorder are discussed.     

网络环境下的个性化信任模型PTM

信任是人类社会的基础,在科技、商业、日常生活等领域发挥着重要作用,一个健全的社会离不开信任。在研究现有信任模型缺陷的基础上,结合现实生活中的各种信任场景,提出了网络环境下的个性化信任模型。该信任模型能够针对不同实体识别出不同的信任意义,在特定的上下文环境中能为用户推荐满足其条件的所有信任路径,具有更好的动态适应性和上下文环境相关性。实验结果表明,该模型可有效提高信任模型的准确率。