Term discrimination for text search tasks derived from negative binomial distribution

Accurate term discrimination in information retrieval is essential for identifying important terms in specific documents. In addition to the widely known inverse document frequency (IDF) method, alternative approaches such as the residual inverse document frequency (RIDF) scheme have been introduced for term discrimination. However, existing methods' performance is not unconditionally convincing. We propose a new collection frequency weighting scheme derived from the negative binomial distribution model of term occurrences. Factorial experiments were performed to examine potential interaction effect between collection frequency weight methods and term frequency weight methods according to the mean average precision and normalized discounted cumulative gain performance assessors. The results indicate that our proposed term discrimination method offers a significant gain in accuracy as compared to the IDF and RIDF scheme. This finding is reinforced by the fact that the results show no interaction effects among factors.     

Automatic indexing using term discrimination and term precision measurements

A variety of abstract automatic indexing models have been developed in recent times in an effort to produce indexing methods that are both effective and usable in practice. Among these are the term discrimination model and the term precision system. These two indexing systems are briefly described and experimental evidence is cited showing that a combination of both theories produces better retrieval performance than either one alone. Appropriate conclusions are reached concerning viable automatic indexing procedures usable in practice.     

Compression of index term dictionary in an inverted-file-orientated database: Some effective algorithms

A new method of index term dictionary compression in an inverted-file-orientated database is discussed. A technique of word coding that generates short fixed-length codes obtained from the index terms themselves by analysis of monogram and bigram statistical distributions is described. Transformation of the index term dictionary into a code dictionary preserves a word-to-word discrimination with a rate of three synonyms per 1300 terms, at compression ratio up to 90% and at low cost in terms of the CPU time expenditure. When applied in computer network environment, it offers substantial savings in communication channel utilization at negligible response time degradation. Experimental data for 26,113 index term dictionary of the New York Times Info Bank available via a computer network are presented.     

What is a genetic test, and why does it matter?

How the term ‘genetic test’ is defined, matters for social policy. The past few years have witnessed many efforts to enact legal barriers specifically against genetic discrimination. To the extent that information derived from genetic tests receives special protection, both enthusiasts for genetic medicine and those who stress its perils have an incentive to adopt a broad interpretation of genetic testing. However, the consequences have not always been those anticpated.     

A framework for understanding Latent Semantic Indexing (LSI) performance

In this paper we present a theoretical model for understanding the performance of Latent Semantic Indexing (LSI) search and retrieval application. Many models for understanding LSI have been proposed. Ours is the first to study the values produced by LSI in the term by dimension vectors. The framework presented here is based on term co-occurrence data. We show a strong correlation between second-order term co-occurrence and the values produced by the Singular Value Decomposition (SVD) algorithm that forms the foundation for LSI. We also present a mathematical proof that the SVD algorithm encapsulates term co-occurrence information.     

Hierarchical gradient- and least squares-based iterative algorithms for input nonlinear output-error systems using the key term separation

This paper considers the parameter identification problems of the input nonlinear output-error (IN-OE) systems, that is the Hammerstein output-error systems. In order to overcome the excessive calculation amount of the over-parameterization method of the IN-OE systems. Through applying the hierarchial identification principle and decomposing the IN-OE system into three subsystems with a smaller number of parameters, we present the key term separation auxiliary model hierarchical gradient-based iterative algorithm and the key term separation auxiliary model hierarchical least squares-based iterative algorithm, which are called the key term separation auxiliary model three-stage gradient-based iterative algorithm and the key term separation auxiliary model three-stage least squares-based iterative algorithm. The comparison of the calculation amount and the simulation analysis indicate that the proposed algorithms are effective.     

7种ESI学科潜力值计算方法比较研究

[目的/意义]在"双一流"战略背景下，应用合理的算法计算未进入ESI机构的潜力值，非常重要。[方法/过程]本文通过ESI和InCites数据库，利用现有的7种学科潜力值计算方法，对内蒙古大学"生物学"学科进行实证研究。[结果/结论]基于内蒙古大学"生物学"在各种算法下的学科潜力值结果，对不同学科潜力值计算方法进行比较研究。     

基于再制造和顾客等待的差别定价模型研究

研究了一种基于再制造和顾客等待的差别定价模型,假设顾客对产品的估价是异质的,当顾客估价低于新产品价格时,可能购买再制造品。研究表明制造商的最优差别定价决策和利润受到再制造成本和顾客等待行为的影响,最后通过仿真算例说明所得的结论。     

A novel term weighting scheme based on discrimination power obtained from past retrieval results

Term weighting for document ranking and retrieval has been an important research topic in information retrieval for decades. We propose a novel term weighting method based on a hypothesis that a term’s role in accumulated retrieval sessions in the past affects its general importance regardless. It utilizes availability of past retrieval results consisting of the queries that contain a particular term, retrieved documents, and their relevance judgments. A term’s evidential weight, as we propose in this paper, depends on the degree to which the mean frequency values for the relevant and non-relevant document distributions in the past are different. More precisely, it takes into account the rankings and similarity values of the relevant and non-relevant documents. Our experimental result using standard test collections shows that the proposed term weighting scheme improves conventional TF^*IDF and language model based schemes. It indicates that evidential term weights bring in a new aspect of term importance and complement the collection statistics based on TF^*IDF. We also show how the proposed term weighting scheme based on the notion of evidential weights are related to the well-known weighting schemes based on language modeling and probabilistic models.     

基于随机前沿的中国勘察设计行业效率影响因素分析

对中国31个省级行政区2006—2011年工程勘察设计行业投入产出面板数据,采用随机前沿分析方法测定各地区的行业生产效率及其变化,并对影响行业非技术效率的因素进行定量计算和回归分析。结果表明:产出函数的技术非效率项对产出具有显著的影响,市场化程度、执业注册人数占比和规模经济同技术非效率项之间存在负向关联,而科研投入和中高级职称人数占比则对技术非效率项具有正向影响;该行业劳动力投入产出弹性(0.672 1)远大于资本投入的产出弹性(0.440 3)。     

金融歧视、金融错配与技术创新

金融发展中的歧视和错配问题是提升技术创新水平亟待破除的藩篱。本文将金融歧视、金融错配与技术创新及其影响因素纳入计量模型，利用我国省际层面的面板数据进行实证考察。结果表明：金融歧视和金融错配对技术创新具有显著的抑制作用；金融歧视强化了金融错配的技术创新抑制效应，且这一影响效应在东、中、西三大区域依次增强。金融错配是金融歧视影响技术创新的重要作用路径，随着金融歧视跨越一定的临界值，金融错配对技术创新的抑制效应更为突出。本文为深化金融和科技体制改革、增强金融服务实体能力提供了有益参考。     

Serum ionised calcium in birth asphyxia

Serum total and ionised calcium levels were measured at birth and at 48 hours in 25 term neonates with birth asphyxia (one minute APGAR score of 6 or less) and in 25 normal term neonates (one minute APGAR score of 7 or more). Infants were categorised into two groups TAGA (term appropriate for gestational age) and TSGA (term small for gestational age). Asphyxiated infants had significantly lower serum total and ionised calcium values at birth as well as at 48 hours. Abnormal clinical features were observed in 48% of asphyxiated infants. Low ionised calcium was detected in symptomatic babies, who had otherwise normal total calcium values. Due to hyocalcemia especially ionised calcium in asphyxiated infants and high frequency of functional derangement associated with this hypocalcemioa, serial monitoring of serum isonised calcium levels is necessary.     

Photoelastic analysis of T-tail stresses

This paper presents the results of an investigation to determine the stress values and distribution in the T-tail connection for pole-pieces used in the construction of high-speed alternating current generators and motors.A comparison is made between the results of the photoelastic studies and the conventional methods of calculation.     

灰色理论在膨胀土胀缩等级分类中的应用

评判指标的选取是影响膨胀土胀缩等级分类的一个重要因素,基于灰色理论中灰色关联分析法和灰色聚类法,采用标准吸湿含水率、塑性指数、自由膨胀率三个反映膨胀土本质特性的指标来判定膨胀土的胀缩等级,并与其它方法对比分析,其计算结果与实际膨胀潜势基本吻合,验证了灰色理论在膨胀土胀缩等级分类中的合理性。     

The computation of discrimination values

Results have been reported showing the usefulness of discrimination value in automatic construction of dictionaries for information retrieval. While discrimination value is defined in the literature, no specific explanation of its computation is given. In this paper the computation of discrimination value is discussed, a relatively efficient algorithm is presented and an example is given.     

The impulse strength of solid and gas-filled high voltage cables

A method is presented that allows the computation of the impulse strength of insulating oil and of solid and gas-filled cables. The principle of the calculation is that breakdown is initiated by currents due to an electronic emission from the cathode; in gas-filled cables these currents are increased by means of gaseous ionization in the butt spaces. Approximate equations are deduced and numerical impulse strength values for insulating oil and solid cable computed, resulting in fair agreement with experimental observations. Extending the equations to gas-filled cables, numerical impulse data for varying gas pressure and for varying radial butt-space alignment are evaluated.     

基于VAR模型的天津市技术转移与区域经济发展动态关系研究

基于天津市区域技术转移基础指标体系的构建及相应综合指数的计算,通过建立区域技术转移综合指数与区域经济增长指数两变量间的向量自回归模型,对天津市区域技术转移与区域经济发展之间的动态关系进行了考察。方差分解结果表明,区域经济的发展所产生的技术需求是拉动区域技术转移的主要动力。技术转移对于经济增长的影响则既是短期的、正向的,同时也是长期的、持续有效的。但技术转移对区域经济增长的整体影响程度还是很低的。针对造成这种状况的原因,提出了相应的政策建议。     

Can the inerter be a successful shock-absorber? The case of a ball-screw inerter with a variable thread lead

This paper investigates an application of a ball-screw inerter for mitigation of impact loadings. The problem of impact absorption is to provide a minimum reaction force that optimally decelerates and eventually stops an impacting object within the available absorber stroke. It significantly differs from vibration mitigation problems which are typical application of inerters. The paper demonstrates that the optimum absorption can be achieved by fully passive means. For known values of the object mass and inerter parameters, the obtained solution is independent of the impact velocity. The optimum passive absorption is achieved by employing a variable thread lead. As a result, two force components emerge, the typical inertance-related force and a damping-like term, and sum up to provide the optimum constant deceleration force. This result is relatively unique: conventional absorbers do not provide a constant force even with complex active control systems. Finally, an optimization problem is formulated to reduce the influence of process uncertainties (range of possible mass values, unknown friction). The results are verified and analyzed in a numerical example.     

NCEP/NCAR再分析数据在风能资源评估中的应用研究

规划风电场短期测风数据的测试相关预测（Measure-Correlate-Predict MCP）是反映风电场风能长期平均水平的主要技术手段,对于预测规划风电场代表年年发电量具有重要意义。然而工程实践中,气象站长期参考数据常受到各类客观因素的影响,数据质量不能满足MCP要求,进而造成对规划风电场风能资源的错误评估。NCEP/NCAR数据是由美国环境预报中心(NCEP)和国家大气研究中心(NCAR)联合推出的再分析数据集,该数据作为一种可替代的长期参考数据得到了广泛的应用。本文对NCEP/NCAR数据在风能资源评估中的应用进行研究,提出了适用于该数据的MCP分析方法——风指数法。通过算例分析后发现,以NCEP/NCAR再分析数据为长期参考数据,风指数法为计算方法的短期测风数据MCP分析原则具有较高的可靠性和工程实用价值。     

Word sense discrimination in information retrieval: A spectral clustering-based approach

Word sense ambiguity has been identified as a cause of poor precision in information retrieval (IR) systems. Word sense disambiguation and discrimination methods have been defined to help systems choose which documents should be retrieved in relation to an ambiguous query. However, the only approaches that show a genuine benefit for word sense discrimination or disambiguation in IR are generally supervised ones. In this paper we propose a new unsupervised method that uses word sense discrimination in IR. The method we develop is based on spectral clustering and reorders an initially retrieved document list by boosting documents that are semantically similar to the target query. For several TREC ad hoc collections we show that our method is useful in the case of queries which contain ambiguous terms. We are interested in improving the level of precision after 5, 10 and 30 retrieved documents (P@5, P@10, P@30) respectively. We show that precision can be improved by 8% above current state-of-the-art baselines. We also focus on poor performing queries.