一种基于用户行为反馈的兴趣度模型更新算法

个性化推荐技术在电子商务系统中得到了广泛应用.针对现有的用户模型不能及时根据用户自身兴趣偏移进行更新的问题,提出了一种基于用户行为反馈的兴趣度模型的更新算法,在创建好模型的基础上,分析用户的购买记录和用户的浏览行为,结合用户的兴趣内容,实现用户兴趣的自动更新,得到的针对新的用户兴趣的推荐商品列表,在此基础上结合用户的购买商品记录,实现推荐商品的个性化排序,从而向用户进行个性化推荐.实验对比结果表明,该算法能更好地发现用户当前的购买兴趣,从而进一步提高个性化推荐精度和用户满意度.     

基于用户购买意愿力的协同过滤推荐算法

针对网购行为中商品浏览量排名靠前而销量滞后的问题, 在用户购买意愿力的基础上, 提出一种增强评分矩阵协同过滤推荐算法. 首先, 利用惩罚因子作为增强型矩阵的评价权重, 加权表征用户购物意愿力的商品画像, 取得增强型矩阵的预测评分; 其次, 融合以基于项目的协同过滤推荐, 建立由潜在兴趣商品间的项目相似度矩阵得到的基础型评分矩阵; 最后, 以TOP-N结果向购买意愿较强的目标用户推荐排名靠前的商品. 实验结果表明: 与传统基于项目的协同过滤推荐算法相比, 增强评分矩阵协同过滤推荐算法的推荐准确率提升2.48%, 召回率提升4.31%, 综合值F₁提升3.19%, 从而有效解决了用户感兴趣商品排名靠后, 且不被购买或购买次数较少的问题, 以达到购买意愿力较强、 目标用户更准的推荐宗旨, 进而提高推荐精度.     

基于中间商品兴趣度加权的内容推荐算法

内容推荐算法是在电子商务网站中应用比较广泛的推荐技术之一,主要针对商品之间属性相似度和用户对商品兴趣度建模.但传统的内容推荐算法不能及时反映用户对商品兴趣度的时间变化,基于这点提出一种基于中间商品兴趣度加权的内容推荐算法.改进算法增加了兴趣度时间权重函数和商品时间权重函数,可以提高商品推荐准确率,仿真试验结果证明该算法是有效的.     

用户偏好建模：考虑长期与短期兴趣因素

鉴于电子商务网站推荐系统的需要,将用户兴趣分为长期兴趣和短暂兴趣,并提出一种基于长期兴趣和短暂兴趣的用户偏好表示法.利用web服务器数据库的数据,采用无监督学习方法,对用户注册信息进行挖掘,提取出用户长期兴趣.基于向量映射,对web服务器日志上的用户使用记录数据和内容数据进行分析,提取用户短暂兴趣.通过用户反馈信息修正"粗糙"用户偏好文档,使得用户偏好文档更新得以实现.最后,应用了实证案例验证了该方法的合理性和有效性.     

基于用户兴趣和项目周期的协同过滤推荐算法

协同过滤推荐算法以没有限定推荐对象类型、无需用户反馈信息等优势在众多个性化推荐算法中脱颖而出。但是现有算法缺乏对用户之间的差异和用户自身的兴趣考虑,对用户和项目之间的潜在关联考虑不充分,这些问题均会影响推荐精度。该文提出一种基于用户兴趣和项目周期的协同过滤推荐算法,该算法在计算相似度时引入用户兴趣权重UI、项目时间等因素,并采用融合因子将改进后所得用户和项目信息进行综合,获得推荐列表。对比实验得出:该算法在推荐精确度上提高了11.034%,研究结果表明:该算法可有效提高推荐精确度。     

基于情感分析和情感遗忘的协同过滤推荐策略

【目的】探索弥补现有协同过滤推荐系统中存在的诸如无法有效地识别用户兴趣的迁移、数据稀疏情况下推荐准确率低等缺陷的方法。【方法】通过对网络用户在线评论信息进行基于方面级的情感分析，利用改进的DP算法提取出评论信息中用户潜在的情感倾向，并对它进行有效地量化，有效地将用户的情感因素引入到用户兴趣建模过程中。同时，引入艾宾浩斯遗忘曲线理论，解决因时间变化而导致的用户兴趣迁移的问题。【结果】模拟实验在所选的两套数据集上进行，分别针对平均绝对误差（MAE）和覆盖率（Coverage）两个常用的性能评价标准，与选定的对比算法进行了对比实验。实验结果显示提出的引入情感分析和遗忘的协同过滤推荐算法能够有效地降低MAE，并能有效地提升Coverage。【结论】提出的算法有效地弥补了兴趣迁移对推荐准确率的影响，提高了系统对商品长尾的发掘能力。     

一种基于位置和时间信息的兴趣点推荐方法

在社交网络中,人们往往会访问自己比较感兴趣和离自己比较近的地方,而兴趣点推荐就是根据用户的兴趣偏好能够有效地帮助用户选择自己比较感兴趣的地点。笔者提出一种基于位置和时间信息的兴趣点推荐方法。该方法从兴趣点的角度出发分为3个步骤,首先使用用户历史访问的兴趣点的位置信息计算用户历史访问兴趣点和用户未曾访问过的兴趣点的相似度;然后使用时间信息,将一天划分为不同的时间段,统计所有兴趣点在一天中不同时间段被签到的次数,计算用户历史访问兴趣点和用户未曾访问过的兴趣点的相似度;最后根据兴趣点的位置和时间信息综合计算用户历史访问兴趣点与用户未曾访问兴趣点的相似度,根据Top-N策略向用户推荐用户未曾访问过的兴趣点。在现实社会中的真实数据集上进行实验验证,实验结果表明笔者提出的方法是有效的。     

考虑商品重复购买周期的协同过滤推荐方法改进

传统基于用户的协同过滤商品推荐方法通常未考虑目标用户是否购买过类似商品以及商品的重复购买周期等因素,由此造成有些商品推荐的时机不对,不仅占用了推荐资源,还可能给消费者带来困扰,为此提出一种基于商品重复购买周期的改进协同过滤推荐方法。在传统协同过滤算法的基础上引入已购商品回购状态变量,根据目标用户的历史购买数据和商品重复购买周期对所购买商品的回购状态进行计算,进而得出不处于回购周期内的已购商品类集,据此对原始推荐结果进行过滤。实验结果表明,改进后的协同过滤推荐系统能有效预测顾客的购买行为,明显提高商品推荐的准确性。     

基于Timed-HITS与协同过滤的混合推荐算法

用户间的信任关系、用户对商品的偏好兴趣及商品的时效性都会影响对商品的推荐效果.将这些因素引入到基本的HITS算法中,对HITS算法进行了改进.将用户对商品的偏好兴趣矩阵进行了改进,利用隐馈数据通过逻辑回归算法估计用户对商品的偏好兴趣,对评分为零的情况赋予了不同的偏好兴趣度,这样更符合实际.将改进的HITS算法和协同过滤算法相结合得到一个混合推荐算法,同时将用户分为活跃用户和非活跃用户分别进行推荐.将提出的算法在Movielens数据集上进行了试验,结果表明该算法在一定程度上缓解了数据稀疏和冷启动的问题,推荐效果优于基于用户的协同过滤算法.     

基于多任务权重参数学习的兴趣点推荐算法研究

基于位置的社交网络的快速发展,通过借助社交网络来分享用户位置信息,其中包含了丰富的上下文信息,比如用户签到、兴趣点地理位置、用户社交关系等,从而对兴趣点推荐的发展提供了很大的机遇.但是,如何有效地利用这些上下文信息,解决数据稀疏和隐式反馈等问题,是很大的挑战.针对这一问题,提出了一种能够动态融合不同上下文因素的推荐算法,该推荐算法可以融合不同类型的上下文因素,比如地理信息、类别信息、时间信息等,通过一种类似梯度下降的动态权重参数学习的方法,动态地学习每个因素的权重,适应不同类型用户特点,从而改善兴趣点推荐效果.     

Markedness and its Interpretation in Language Use

Language markedness is a common phenomenon in languages, and is reflected from hearing, vision and sense, i.e. the variation in the three aspects such as phonology, morphology and semantics. This paper focuses on the interpretation of markedness in language use following the three perspectives, i.e. pragmatic interpretation, psychological interpretation and cognitive interpretation, with an aim to define the function of markedness.     

Features of Women's language

Language is a means of verbal communication. People use language to communicate with each other. In the society, no two speakers are exactly alike in the way of speaking. Some differences are due to age, gender, statue and personality. Above all, gender is one of the obvious reasons. The writer of this paper tries to describe the features of women＇s language from these perspectives： pronunciation, intonation, diction, subjects, grammar and discourse. From the discussion of the features of women＇s language, more attention should be paid to language use in social context. What＇s more, the linguistic phenomena in a speaking community can be understood more thoroughly.     

Characterization of Ordovician carbonate reservoirs, southeastern Saskatchewan, Canada

The discovery of the prolific Ordovician Red River reservoirs in 1995 in southeastern Saskatchewan was the catalyst for extensive exploration activity which resulted in the discovery of more than 15 new Red River pools. The best yields of Red River production to date have been from dolomite reservoirs. Understanding the processes of dolomitization is, therefore, crucial for the prediction of the connectivity, spatial distribution and heterogeneity of dolomite reservoirs.The Red River reservoirs in the Midale area consist of 3～4 thin dolomitized zones, with a total thickness of about 20 m, which occur at the top of the Yeoman Formation. Two types of replacement dolomite were recognized in the Red River reservoir: dolomitized burrow infills and dolomitized host matrix. The spatial distribution of dolomite suggests that burrowing organisms played an important role in facilitating the fluid flow in the backfilled sediments. This resulted in penecontemporaneous dolomitization of burrow infills by normal seawater. The dolomite in the host matrix is interpreted as having occurred at shallow burial by evaporitic seawater during precipitation of Lake Almar anhydrite that immediately overlies the Yeoman Formation. However, the low δ18O values of dolomited burrow infills (-5.9‰～ -7.8‰, PDB) and matrix dolomites (-6.6‰～ -8.1‰, avg. -7.4‰ PDB) compared to the estimated values for the late Ordovician marine dolomite could be attributed to modification and alteration of dolomite at higher temperatures during deeper burial, which could also be responsible for its 87Sr/86Sr ratios (0.7084～0.7088) that are higher than suggested for the late Ordovician seawaters (0.7078～0.7080). The trace amounts of saddle dolomite cement in the Red River carbonates are probably related to "cannibalization" of earlier replacement dolomite during the chemical compaction.     

低渗透非均质砂岩油藏启动压力梯度研究

理论推导与室内实验相结合,建立了低渗透非均质砂岩油藏启动压力梯度确定方法。首先借助油藏流场与电场相似的原理,推导了非均质砂岩油藏启动压力梯度计算公式。其次基于稳定流实验方法,建立了非均质砂岩油藏启动压力梯度测试方法。结果表明:低渗透非均质砂岩油藏的启动压力梯度确定遵循两个等效原则。平面非均质油藏的启动压力梯度等于各级渗透率段的启动压力梯度关于长度的加权平均;纵向非均质油藏的启动压力梯度等于各渗透率层的启动压力梯度关于渗透率与渗流面积乘积的加权平均。研究成果可用于有效指导低渗透非均质砂岩油藏的合理井距确定,促进该类油藏的高效开发。     

On Tragic Consciousness In The Works By Ernest Hemingway

As an American modern novelist who were famous in the literary world, Hemingway was not a person who always followed the trend but a sharp observer. At the same time, he was a tragedy maestro, he paid great attention on existence, fate and end-result. The dramatis personae's tragedy of his works was an extreme limit by all means tragedy on the meaning of fearless challenge that failed. The beauty of tragedy was not produced on the destruction of life, but now this kind of value was in the impact activity. They performed for the reader about the tragedy on challenging for the limit and the death.     

A computer generator for randomly layered structures

AcomputergeneratorforrandomlylayeredstructuresYUJia shun1,2,HEZhen hua2(1.TheInstituteofGeologicalandNuclearSciences,NewZealand;2.StateKeyLaboratoryofOilandGasReservoirGeologyandExploitation,ChengduUniversityofTechnology,China)Abstract:Analgorithmisintrod…     

An Index mechanism for multi-scale view in spatial databases

There are numerous geometric objects stored in the spatial databases. An importance function in a spatial database is that users can browse the geometric objects as a map efficiently. Thus the spatial database should display the geometric objects users concern about swiftly onto the display window. This process includes two operations:retrieve data from database and then draw them onto screen. Accordingly, to improve the efficiency, we should try to reduce time of both retrieving object and displaying them. The former can be achieved with the aid of spatial index such as R-tree, the latter require to simplify the objects. Simplification means that objects are shown with sufficient but not with unnecessary detail which depend on the scale of browse. So the major problem is how to retrieve data at different detail level efficiently. This paper introduces the implementation of a multi-scale index in the spatial database SISP (Spatial Information Shared Platform) which is generalized from R-tree. The difference between the generalization and the R-tree lies on two facets: One is that every node and geometric object in the generalization is assigned with a importance value which denote the importance of them, and every vertex in the objects are assigned with a importance value,too. The importance value can be use to decide which data should be retrieve from disk in a query. The other difference is that geometric objects in the generalization are divided into one or more sub-blocks, and vertexes are total ordered by their importance value. With the help of the generalized R-tree, one can easily retrieve data at different detail levels.Some experiments are performed on real-life data to evaluate the performance of solutions that separately use normal spatial index and multi-scale spatial index. The results show that the solution using multi-scale index in SISP is satisfying.     

Jane Eyre——A Feminist In The 19th Century

In the 19th century the society was controlled by men, and women were just appendants of them, they had not any rights and freedom. But Jane was an exception, she showed some characteristics of early feminist. Jane showed her characteristics of feminism in three aspects: rebellion, equality, and independence. These characteristics were helpful to her success, and feminism is the only way out for women of that time.     

Achieving Unusual States of Matter Under High Pressure

正The periodicity of the elements and the non-reactivity of the inner-shell electrons are two related principles of chemistry,rooted in the atomic shell structure.Within compounds,Group I elements,for example,invariably assume the+1 oxidation state,and their chemical properties differ completely from those of the p-block elements.These general rules govern our understanding of chemical structures and reactions.Using first principles calcula-     

Exchange-Correlation and Electronic Excitation Energies from Pairing Matrix Fluctuations

We have developed an adiabatic connection to formulate the ground-state exchange-correlation energy in terms of pairing matrix linear fluctuations.This formulation of the exchange-correlation energy opens a new channel for density functional approximations based on the many-body perturbation theory.We illustrate the potential of such approaches with an approximation based on the particle-particle Random Phase Approximation(pp-RPA).This re-