Research on the User Interest Modeling of Personalized Search Engine

At present, how to enable Search Engine to construct user personal interest model initially, master user＇s personalized information timely and provide personalized services accurately have become the hotspot in the research of Search Engine area. Aiming at the problems of user model＇s construction and combining techniques of manual customization modeling and automatic analytical modeling, a User Interest Model （UIM） is proposed in the paper. On the basis of it, the corresponding establishment and update algorithms of User lnterest Profile （UIP） are presented subsequently. Simulation tests proved that the UIM proposed and corresponding algorithms could enhance the retrieval precision effectively and have superior adaptability.

BP Network Based Users’Interest Model in Mining WWW Cache

By analyzing the WWW Cache model, we bring forward a user-interest description method based on the fuzzy theory and user-interest inferential relations based on BP（baek propagation） neural network. By this method, the users＇ interest in the WWW cache can be described and the neural network of users＇ interest can be constructed by positive spread of interest and the negative spread of errors. This neural network can infer the users＇ interest. This model is not the simple extension of the simple interest model, but the round improvement of the model and its related algorithm.

Learning Hierarchical User Interest Models from Web Pages

We propose an algorithm for learning hierarchical user interest models according to the Web pages users have browsed. In this algorithm, the interests of a user are represented into a tree which is called a user interest tree, the content and the structure of which can change simultaneously to adapt to the changes in a user＇s interests. This expression represents a user＇s specific and general interests as a continuurn. In some sense, specific interests correspond to shortterm interests, while general interests correspond to longterm interests. So this representation more really reflects the users＇ interests. The algorithm can automatically model a us er＇s multiple interest domains, dynamically generate the in terest models and prune a user interest tree when the number of the nodes in it exceeds given value. Finally, we show the experiment results in a Chinese Web Site.

Research on Bayesian Network Based User's Interest Model

It has very realistic significance for improving the quality of users＇ accessing information to filter and selectively retrieve the large number of information on the Internet. On the basis of analyzing the existing users＇ interest models and some basic questions of users＇ interest （representation, derivation and identification of users＇ interest）, a Bayesian network based users＇ interest model is given. In this model, the users＇ interest reduction algorithm based on Markov Blanket model is used to reduce the interest noise, and then users＇ interested and not interested documents are used to train the Bayesian network. Compared to the simple model, this model has the following advantages like small space requirements, simple reasoning method and high recognition rate. The experiment result shows this model can more appropriately reflect the user＇s interest, and has higher performance and good usability.

Pricing Stochastic Barrier Options under Hull-White Interest Rate Model

A barrier option valuation model with stochastic barrier which was regarded as the main feature of the model was developed under the Hull-White interest rate model.The purpose of this study was to deal with the stochastic barrier by means of partial differential equation methods and then derive the exact analytical solutions of the barrier options.Furthermore,a numerical example was given to show how to apply this model to pricing one structured product in realistic market.Therefore,this model can provide new insight for future research on structured products involving barrier options.

RUIN PROBABILITY IN A SEMI-MARKOV RISK MODEL WITH CONSTANT INTEREST FORCE AND HEAVY-TAILED CLAIMS

In the present paper, we consider a kind of semi-Markov risk model （SMRM） with constant interest force and heavy-tailed claims~ in which the claim rates and sizes are conditionally independent, both fluctuating according to the state of the risk business. First, we derive a matrix integro-differential equation satisfied by the survival probabilities. Second, we analyze the asymptotic behaviors of ruin probabilities in a two-state SMRM with special claim amounts. It is shown that the asymptotic behaviors of ruin probabilities depend only on the state 2 with heavy-tailed claim amounts, not on the state 1 with exponential claim sizes.

On the Distribution of Duration of First Negative Surplus for a Discrete Time Risk Model with Random Interest Rate

In this paper, we examine further annuity-due risk model presented by Cai （Probability in the Engineering and Informational Sciences, 16（2002）, 309-324）. We consider the computation for the distribution of duration of first negative surplus and the algorithm is shown for calculating probability that ruin occurs and the duration of first negative surplus takes any nonnegative integers values. Numerical illustration for the main result is given.

Models of the Short Interest Rate in Discrete Processes

The modeling of the term structure of interest rates is one of primary topics for researches in financial economics. Here we consider models of the short interest rate in discrete processes. Our methodology of analysis follows the framework of discrete stochastic calculus.

乡村振兴背景下小农户与新农人合作的利益联结模式选择研究

基于2021年中国6个省份的小农户调研数据,采用有序Probit模型,从小农户的个体特征、家庭特征、生产经营状况、市场状况以及与新农人合作目的等5个方面探讨影响小农户与新农人建立利益联结模式选择的关键因素。结果表明:现阶段小农户与新农人合作以松散型的利益联结模式为主,但地区之间仍存在差异,中西部地区小农户更倾向于选择紧密型的利益联结模式;从影响因素来看,家庭农业经营收入比例、风险承受能力、是否加入合作组织、是否在涉农企业就业等对小农户选择紧密的利益联结模式起到显著的正向影响,而受教育程度、保证农产品销路对小农户利益联结模式选择起着显著的负向影响。据此,建议培育发展农业专业合作组织,发展壮大涉农企业,加大政府政策支持,提高小农户的风险承受能力,以期助力小农户与新农人构建乡村利益共同体。

Establishing a Social Governance Model Based on Collaboration,Participation,and Common Interests:Value,Structure and Roadmap

The 19th National Congress of the Communist Party of China(CPC)put forward the proposal of establishing a social governance model based on collaboration,participation,and common interests,with the aim of developing new approaches to social governance and further modernizing China’s social system and capacity for governance.As a structuralized social relation addressing diversified governance bodies,the model has consolidated the social governance innovations achieved since the 18th CPC National Congress.Focusing on three dimensions—"value,""structure"and"roadmap,"this paper tries to interpret the value connotations and defining features behind the model and explores its development roadmap.Such a social governance model is a response to political,social and public value appeals,and an adjustment to the order of governance bodies,resource allocations and the benefit distribution structure.Its construction is a systematic and long-term project,which should aim continuously at satisfying people’s ever-higher needs,perfecting laws and regulations,cultivating a pool of specialized organizations and talents,exerting the technology advantages of the Internet in governance,and promoting socialization,legalization,specialization and intellectualization in social development.

Continuance intention to use the mobile interest-based community: An integrated theoretical model and empirical study

Purpose： This paper aims at an understanding of factors that influence the continuance intention to use mobile interest-based community applications, with a focus on the impacts of technology acceptance model （TAM） constructs and experiential value. Design/methodology/approach： Taking a hybrid model combining TAM and extended expectation confirmation model （ECM） as foundation, this study integrated experiential value into the research model. A survey method was adopted and the sample was constituted by 347 Chinese undergraduates who were experienced users of mobile interest-based community applications. Structural equation modeling was used to test the research model. Findings： Our findings suggest that 1） key determinants of user satisfaction with mobile interest-based community applications are confirmation, perceived usefulness （PU）, perceived ease of use （PEU） and experiential value. Both satisfaction and PU are directly correlated with continuance intention; 2） PU＇s impact on satisfaction and continuance intention has been confirmed again in this study. Although PEU has no direct impact on satisfaction and continuance intention, it may indirectly affect them via PU; 3） all the perceived experiential values （aesthetics, playfulness, service excellence and return on investment） have a positive influence on satisfaction. Research limitations： We did not examine the effects of individual user differences that may also be important for understanding satisfaction and continuance intention. Practical implications： The study findings can help service providers improve the use of mobile interest-based community applications. Originality/value： Our study contributes to a more systematic understanding of factors that influence continuous use of mobile interest-based community applications.

基于用户兴趣模型的个性化旅游线路生成建模研究

针对个性化旅游线路生成过程中用户个人喜好分析环节较为薄弱,依照用户兴趣分析结果生成路线景点过于分散,旅游线路景区覆盖率较低的问题,提出一种基于用户兴趣模型的个性化旅游线路生成建模方法。获取用户数据,并按照显性兴趣、隐性兴趣的分类方式设定数据标签,完成数据预处理。根据关联规则结合数据预处理结果,构建用户兴趣模型,分析用户对部分旅游目的地的兴趣值以及用户的旅游行为特征。基于用户兴趣模型的个性化旅游线路生成建模方法设计完成。实验结果证实,所提模型可有效克服用户个人喜好分析问题,提升旅游线路景区覆盖率。

冒充性攻击下无线传感节点信息数据安全推荐算法

冒充性攻击伪装成合法的通信实体,向无线传感网络中的传感节点发送虚假的信息或命令,降低了网络信息数据推荐的效率,影响网络安全性。为此,研究了一种冒充性攻击下的无线传感信息数据安全推荐算法,以保证通信质量。计算冒充性攻击下的无线传感网络邻居节点的信任度,从中选取信任度取值比较高的节点组建备选推荐无线传感节点集合。对备选节点推荐集合展开数据去噪、冒充性攻击检测和重构处理,同时将用户自定义标签映射为标准标签,以此建立可躲避攻击节点模型。获取可躲避攻击的无线传感节点进行组网。仿真结果表明,所提算法在冒充性攻击下,查全率高于88%、平均响应时间低于390 ms、MAE和RMAE低于1.09%和0.95%。证明所提算法无线传感节点信息数据推荐效果较好,提高了无线传感网络通信质量和通信效率,保证了传输安全性和可靠性。

融合兴趣主题矩阵和主题生命树的社交用户长短兴趣挖掘

[目的/意义]针对当前社交用户兴趣挖掘效果不理想,且缺乏对兴趣类型特征的深入研究,提出一种新的长短兴趣挖掘方法。[方法/过程]首先引入兴趣价值参数作为先验知识对Labeled LDA主题模型进行改进,依据改进的主题模型挖掘不同时间窗口的兴趣主题,构建兴趣主题矩阵。然后基于用户兴趣的变化规律构建主题生命树,挖掘用户兴趣的生命特征和潜在关联,将用户兴趣划分为长期兴趣、短期兴趣和过期兴趣。最后依据兴趣主题的强度和波动幅度量化用户不同类型兴趣的权重,实现对用户兴趣的准确表示。[结果/结论]实验采用从新浪微博爬取的真实数据作为训练集和测试集,与已有的兴趣挖掘方法进行比较,结果发现长短兴趣挖掘方法在F1值和MRR值上最高分别提升了7.68%和7.41%。[局限]仅利用微博文本信息对方法进行验证,缺乏对跨平台信息的深入探讨。

考虑数据稀疏性的图书推荐协同过滤算法仿真

图书推荐算法易忽略数据稀疏性问题,导致推荐结果与用户感兴趣内容之间存在较大的偏差。在考虑数据稀疏性的基础上提出一种图书推荐协同过滤算法,对数据预处理,通过对用户和用户之间综合信任度分析,利用分布估计算法对用户兴趣建模;构建用户兴趣簇类集,划分用户兴趣,从中选择出与检索对象最接近的邻居;计算邻近项目得分,按照从大到小的顺序排列,排名靠前的资源项即为图书推荐结果。实验结果表明,所提方法在推荐500本图书时,用时在12s内,且降低了平均绝对误差和均方根误差,实现了最精准的图书推荐。

合约安排与小农户增收——对“小农户+合作社”体系中三种典型利益联结模式的考察

既有研究独立探讨了小农户与合作社之间多种利益联结模式的各自增收效果,但对于什么样的利益联结模式能够更好地促进小农户增收尚无定论。为此,本文构建了一个集消费与生产于一体的农户模型以分析合约安排与小农户增收的因果关系,并基于CLES(2020—2022年)数据对三种典型利益联结模式的增收效果展开实证检验和比较研究。研究表明:第一,合约安排与小农户增收存在正向因果关系,增收效果从低到高依次为“租地+雇工”模式、合同农业模式和股份合作模式。这一结论在考虑遗漏变量估计偏误、内生性检验、替换样本等一系列稳健性检验之后依然成立。第二,小农户依托合约安排通过土地转出和劳动时间再配置(“租地+雇工”模式)、产品溢价(合同农业模式),以及提升产业价值份额(股份合作模式)等路径实现有效增收。本文研究有效识别了小农户与合作社合约安排的三种典型利益联结模式的增收差异及其作用机制,为实现小农户和现代农业发展有机衔接提供了倾向性增收模式与实现路径的理论支撑。

企业公开数据的权益保护路径探析——基于“代码自治”视角

数字经济时代,数据成为新的生产要素,但目前企业公开数据的保护机制缺位。我国司法裁判历程表明数据产权立法已成为必然趋势,但学界受数据单一保护模式的思维禁锢,针对究竟是数据“权利”还是数据“权益”问题争论不休。企业公开数据的动态性使数据赋权面临客体界定困境,权益保护模式能有效解决确权技术难题,为数据产权的构建和完善提供过渡性和兜底性保护。企业在权益保护模式下遵循“禁止之外皆自由”原则,通过“代码自治”和市场机制建立数据私人秩序,法律仅提供补充性救济。从立法论视角出发,可在《反不正当竞争法》中设立商业数据专条,针对限定公开数据和完全公开数据分别设定行为规制标准。从解释论视角出发,应明确数据产品的财产属性,类推物之占有解释代码空间权益,未经授权或者超越授权访问、获取、利用和处分数据的行为均会被认定为破坏了企业对代码空间的完整管领状态,应予以规制。

关于当前商业银行盈利模式的调查——以衢州市为例

近年来在各项政策的推动下,贷款利率持续下行,利差1逐步收窄,信贷市场呈现“以价换量”的竞争格局,商业银行以利差为主要利润来源的盈利模式面临较大的挑战。本文通过分析近年来存贷利差的演变和均衡利差的界定得到,当前信贷市场竞争已较为充分,商业银行总体利差接近合理水平。未来在支持实体经济发展的同时,推动融资成本稳中有降的路径应重点从降低商业银行负债端利率和强化成本控制两方面出发。

基于情境-个体兴趣的药剂学混合式课堂实践

文章基于“情境-个体兴趣”的药剂学混合式教学模式进行课堂实践,结果显示该模式有助于提高学生的学习兴趣和积极性,稳定提升学生成绩,也有利于提升教师的教学效率。此外,还需要完善线上药剂学教学平台,加强与现代智慧教学技术的深度融合,合理运用教学评价模型,探索更加科学客观的教学效果评价方法,促进教学质量的不断提高。