Revisiting the cluster-based paradigm for implicit search result diversification

To cope with ambiguous and/or underspecified queries, search result diversification (SRD) is a key technique that has attracted a lot of attention. This paper focuses on implicit SRD, where the subtopics underlying a query are unknown. Many existing methods appeal to the greedy strategy for generating diversified results. A common practice is using a heuristic criterion for making the locally optimal choice at each round. As a result, it is difficult to know whether the failures are caused by the optimization criterion or the setting of parameters. Different from previous studies, we formulate implicit SRD as a process of selecting and ranking k exemplar documents through integer linear programming (ILP). The key idea is that: for a specific query, we expect to maximize the overall relevance of the k exemplar documents. Meanwhile, we wish to maximize the representativeness of the selected exemplar documents with respect to the non-selected documents. Intuitively, if the selected exemplar documents concisely represent the entire set of documents, the novelty and diversity will naturally arise. Moreover, we propose two approaches ILP4ID (Integer Linear Programming for Implicit SRD) and AP4ID (Affinity Propagation for Implicit SRD) for solving the proposed formulation of implicit SRD. In particular, ILP4ID appeals to the strategy of bound-and-branch and is able to obtain the optimal solution. AP4ID being an approximate method transforms the target problem as a maximum-a-posteriori inference problem, and the message passing algorithm is adopted to find the solution. Furthermore, we investigate the differences and connections between the proposed models and prior models by casting them as different variants of the cluster-based paradigm for implicit SRD. To validate the effectiveness and efficiency of the proposed approaches, we conduct a series of experiments on four benchmark TREC diversity collections. The experimental results demonstrate that: (1) The proposed methods, especially ILP4ID, can achieve substantially improved performance over the state-of-the-art unsupervised methods for implicit SRD. (2) The initial runs, the number of input documents, query types, the ways of computing document similarity, the pre-defined cluster number and the optimization algorithm significantly affect the performance of diversification models. Careful examinations of these factors are highly recommended in the development of implicit SRD methods. Based on the in-depth study of different types of methods for implicit SRD, we provide additional insight into the cluster-based paradigm for implicit SRD. In particular, how the methods relying on greedy strategies impact the performance of implicit SRD, and how a particular diversification model should be fine-tuned.     

供热系统的优化设计及其计算方法

本文介绍应用整数线性规划进行供热系统优化设计的决策方法,同时简单探讨了计算方法。     

Seeing Library Data: A Prototype Data Visualization Application for Librarians

Visualizations can add value to raw library data. Tools that programmatically make such visualizations interactive can further increase the value of these data by giving librarians visual tools to analyze their datasets. To demonstrate these benefits, Kingsborough Community College Library built SeeCollections (http://b7jl.org/seecollections), a Web application that visualizes the libraries’ collections of books and e-books. This article discusses the how SeeCollections gathers data from Kingsborough's discovery layer API (Application Programming Interface) and transforms these data to create visualizations for the Web. SeeCollections is a lightweight, proof-of-concept data application based on a vendor API. API data are often accessible in academic libraries but are frequently underutilized. SeeCollections was built to demonstrate the immediate value of these API data sources to Kingsborough librarians by providing a visual interface to discovery layer data. Keeping in mind the broader literature on data visualization, this article will explore how SeeCollections was built.     

数据库查询定位的开发技巧

以学生课程设计应用系统为背景,介绍了VFP查询系统的一些实现技巧,具体包括任务进度条的实现、用宏命令实现组合查询、删除查询表中的空记录、中英文输入法自动切换、整条记录突出显示以及用Grid模拟Browse窗口等．     

SWOT分析在旅游规划中的应用——以广西北海为例

SWOT分析法是战略规划研究的一种分析技术,指的是对现实的优势、劣势、机遇和挑战进行客观且综合的分析。近几年来该方法逐渐在国土资源规划、城市战略发展规划、旅游规划等方面得到了广泛应用。在北部湾经济圈上升到国家经济发展战略层面的背景下,本文拟试用SWOT分析法对北海在旅游战略规划作初步的分析。     

在线性规划教学中培养学生数学建模能力初探

本文主要阐述如何在线性规划教学中培养学生数学建模能力,让学生了解如何运用所学的线性规划知识去分析和解决实际问题,提高学生的应用能力和创新能力.     

应用型本科网络程序设计课程教学改革研究

以高等教育的目标转变为背景,探讨了网络程序设计课程教学中存在的主要问题,基于构建主义的理论提出了包括重组课程内容体系、加强实践教学等在内的改革思路,对同等类型网络程序设计教学改革提出了建议。     

基于二维零件数控加工图形编程系统研究

随着自动编程技术的迅速发展,各种新型数控编程系统不断出现.利用图形编程理论,针对数控线切割机床的加工特点,开发了一种基于二维零件数控加工的TXBCH图形编程系统,重点研究了系统中图素的概念、图素的定义方式和算法,并在此基础上开发出了相应的软件.通过三十多个不同类型零件的图形输入,验证了本文所开发的TXBCH图形编程系统的正确性.解决了中小企业由于费用问题不能购买大型数控编程系统的难题,加快了中小企业的自动化进程.     

基于对数变换的凸二次规划不可行内点算法

基于对数变换和不可行内点算法,对凸二次规划提出了一种新的迭代方向原始-对偶不可行内点算法,并证明了算法的全局收敛性和多项式复杂性,该算法可以看做近期Pan等人关于线性规划算法的推广.     

高职高专院校教育科学规划课题申报工作的指导

“十五”、“十一五”期间,湖南高职高专院校申报省级教育科学规划课题立项率比较低,除了条件、氛围、机制、基础等因素比本科高校较差外,也有其自身原因。如果所在单位能从课题管理的角度,进一步明确省级教育规划课题内涵,加强课题选题、“活页”设计以及评审书填报的指导,提高高职高专课题申报人的自身素质,是完全有可能提高课题申报的成功率的。