Ambiguous author query detection using crowdsourced digital library annotations

The name ambiguity problem is especially challenging in the field of bibliographic digital libraries. The problem is amplified when names are collected from heterogeneous sources. This is the case in the Scholarometer system, which performs bibliometric analysis by cross-correlating author names in user queries with those retrieved from digital libraries. The uncontrolled nature of user-generated annotations is very valuable, but creates the need to detect ambiguous names. Our goal is to detect ambiguous names at query time by mining digital library annotation data, thereby decreasing noise in the bibliometric analysis. We explore three kinds of heuristic features based on citations, metadata, and crowdsourced topics in a supervised learning framework. The proposed approach achieves almost 80% accuracy. Finally, we compare the performance of ambiguous author detection in Scholarometer using Google Scholar against a baseline based on Microsoft Academic Search.     

Evaluating a digital library self-archiving service: The BDBComp user case study

In this article, we present an overview of a self-archiving service for the Brazilian Digital Library of Computing (BDBComp) and describe a user experiment conducted to evaluate it. This experiment involved several potential real users, including computer science graduate students and professors, and archivists/librarians. The results of this study and their implications for similar services are described and analyzed, following sound statistical principles, which can serve as a basis for other similar studies. These results and their analysis indicate that we have successed in building a usable, efficient and learnable self-archiving service, properties which are essential to bring users to the system.     

当前图书馆数字参考服务的瓶颈与革新措施

针对目前图书馆数字参考服务中存在的典型问题进行分析,归纳了图书馆数字参考服务在发展过程中所面临的瓶颈问题。深入研究图书馆数字参考服务的目的、价值和应用过程,指出了图书馆数字参考服务未来的发展趋势。结合目前图书馆所能够提供的数字参考服务方式、途径及内容,研究切合实际的图书馆数字参考服务革新措施,依次解决目前图书馆数字参考服务发展中所面临的瓶颈问题。     

A reliable FAQ retrieval system using a query log classification technique based on latent semantic analysis

To obtain high performances, previous works on FAQ retrieval used high-level knowledge bases or handcrafted rules. However, it is a time and effort consuming job to construct these knowledge bases and rules whenever application domains are changed. To overcome this problem, we propose a high-performance FAQ retrieval system only using users’ query logs as knowledge sources. During indexing time, the proposed system efficiently clusters users’ query logs using classification techniques based on latent semantic analysis. During retrieval time, the proposed system smoothes FAQs using the query log clusters. In the experiment, the proposed system outperformed the conventional information retrieval systems in FAQ retrieval. Based on various experiments, we found that the proposed system could alleviate critical lexical disagreement problems in short document retrieval. In addition, we believe that the proposed system is more practical and reliable than the previous FAQ retrieval systems because it uses only data-driven methods without high-level knowledge sources.     

“What is a good digital library?” – A quality model for digital libraries

In this article, we elaborate on the meaning of quality in digital libraries (DLs) by proposing a model that is deeply grounded in a formal framework for digital libraries: 5S (Streams, Structures, Spaces, Scenarios, and Societies). For each major DL concept in the framework we formally define a number of dimensions of quality and propose a set of numerical indicators for those quality dimensions. In particular, we consider key concepts of a minimal DL: catalog, collection, digital object, metadata specification, repository, and services. Regarding quality dimensions, we consider: accessibility, accuracy, completeness, composability, conformance, consistency, effectiveness, efficiency, extensibility, pertinence, preservability, relevance, reliability, reusability, significance, similarity, and timeliness. Regarding measurement, we consider characteristics like: response time (with regard to efficiency), cost of migration (with respect to preservability), and number of service failures (to assess reliability). For some key DL concepts, the (quality dimension, numerical indicator) pairs are illustrated through their application to a number of “real-world” digital libraries. We also discuss connections between the proposed dimensions of DL quality and an expanded version of a workshop’s consensus view of the life cycle of information in digital libraries. Such connections can be used to determine when and where quality issues can be measured, assessed, and improved – as well as how possible quality problems can be prevented, detected, and eliminated.     

Wikipedia bi-linear link (WBLM) model: A new approach for measuring semantic similarity and relatedness between linguistic concepts using Wikipedia link structure

Wikipedia links its articles by manually defined semantic relations called the Wikipedia hyperlink (link) structure. The existing Wikipedia link-based semantic similarity (SS) and semantic relatedness (SR) computation models, such as Wikipedia one-way link (WOLM) model and Wikipedia two-way link (WTLM) model, do not assess the strengths of the relationships between a candidate concept and its links (out-links or in-links). These models treat all the links as equally important even though some links are semantically more influential than others and should be given more importance. This phenomenon reduces the accuracy of these models. This paper presents the Wikipedia bi-linear link (WBLM) model that extends the previously proposed WOLM and WTLM models. The WBLM model explores the Wikipedia link structure as a semantic graph and discovers the strongly (bi-linear links) and weakly (out-links or in-links) connected links of a candidate concept. It improves the link-based vector representations of concepts by assigning weights to their connected links according to the strengths of their semantic associations. The experimental results demonstrate that the proposed WBLM model significantly improves the SS and SR computation accuracy of the WOLM model (6.9%, 8%, 24%, 17.3%, 31.2%, 30.6%, 26.5%, and 35.4%) and WTLM model (1.2%, 3.9%, 7.1%, 9.9%, 11%, 6.3%, 12.7%, and 13%), in terms of linear correlations with human judgments on gold standard benchmarks, including MC30, RG65, WS203, SimLex, 353All, MTurk287, MTurk771, and MEN3000, respectively. Moreover, this research offers a deep insight into the Wikipedia link structure and provides an adequate base for understanding it as a semantic graph.     

Text summarization using a trainable summarizer and latent semantic analysis

This paper proposes two approaches to address text summarization: modified corpus-based approach (MCBA) and LSA-based T.R.M. approach (LSA + T.R.M.). The first is a trainable summarizer, which takes into account several features, including position, positive keyword, negative keyword, centrality, and the resemblance to the title, to generate summaries. Two new ideas are exploited: (1) sentence positions are ranked to emphasize the significances of different sentence positions, and (2) the score function is trained by the genetic algorithm (GA) to obtain a suitable combination of feature weights. The second uses latent semantic analysis (LSA) to derive the semantic matrix of a document or a corpus and uses semantic sentence representation to construct a semantic text relationship map. We evaluate LSA + T.R.M. both with single documents and at the corpus level to investigate the competence of LSA in text summarization. The two novel approaches were measured at several compression rates on a data corpus composed of 100 political articles. When the compression rate was 30%, an average f-measure of 49% for MCBA, 52% for MCBA + GA, 44% and 40% for LSA + T.R.M. in single-document and corpus level were achieved respectively.     

Efficient probabilistic XML query processing using an extended labeling scheme and a lightweight index

Recently there is a growing interest in the data model and query processing for probabilistic XML data. There are many potential applications of probabilistic data, and the XML data model is suitable to represent hierarchical information and data uncertainty of different levels naturally. However, the previously proposed probabilistic XML data models and query processing techniques separate finding data matches with evaluating the probabilities of results. Therefore, they should repeatedly access the data and need to get full data of paths given in queries to calculate the probabilities of results.     

A study of the information needs of the users of a folk music library and the implications for the design of a digital library system

A qualitative study of user information needs is reported, based on a purposive sample of users and potential users of the Vaughan Williams Memorial Library, a small specialist folk music library in North London. The study set out to establish what the users’ (both existing and potential) information needs are, so that the library’s online service may take them into account with its design. The information needs framework proposed by Nicholas [Nicholas, D. (2000) Assessing information needs: tools, techniques and concepts for the internet age. London: ASLIB] is used as an analytical tool to achieve this end. The demographics of the users were examined in order to establish four user groups: Performer, Academic, Professional and Enthusiast. Important information needs were found to be based on social interaction, and key resources of the library were its staff, the concentration of the collection and the library’s social nature. A collection of broad design requirements are proposed based on the analysis and this study also provides some insights into the issue of musical relevance, which are discussed.     

Applying scenario-based design and claims analysis to the design of a digital library of geography examination resources

This paper describes the application of Carroll’s scenario-based design and claims analysis as a means of refinement to the initial design of a digital library of geographical resources (GeogDL) to prepare Singapore students to take a national examination in geography. GeogDL is built on top of G-Portal, a digital library providing services over geospatial and georeferenced Web content.Beyond improving the initial design of GeogDL, a main contribution of the paper is making explicit the use of Carroll’s strong theory-based but undercapitalized scenario-based design and claims analysis that inspired recommendations for the refinement of GeogDL.The paper concludes with an overview of the implementation of some of the recommendations identified in the study to address “usability” and “usefulness” design issues in GeogDL, and discusses implications of the findings in relation to geospatial digital libraries in general.     

Digital transformation and European small and medium enterprises (SMEs): A comparative study using digital economy and society index data

Digital transformation is profoundly transforming SMEs' business activities, bringing about comparative advantages and associated risks. Previous studies on digital transformation and SMEs focus on technology adoption, innovation, new value creation, and dynamic capabilities. However, it is unclear how digital technology affects SMEs' specific business activities. We study SMEs' customer access, increasing competition, external funding or access to finance, rising input costs, skilled labor shortages, exogenous shocks, global crises, and regulatory issues. This study aims to fill the literature gap by exploring the impact of digital technology, using digital economy and society index (DESI) as proxies for the SME issues. We use DESI and SME data from a survey on European enterprises’ access to finance. We find that digital transformation strengthens SMEs' ability and flexibility to address main business issues. Furthermore, findings reveal that digitally transformed SMEs have fewer concerns about access to new and traditional customers, competition changes, access to finance, increasing input costs, external shocks, and regulatory changes. However, digital transformation also brings risks, such as the shortage of skilled labor and experienced managers and loss of inherent competitiveness. The novelty of our work lies in supplying quantitative knowledge on the link between digital transformation and European SMEs' critical business concerns. These findings substantially increase our understanding of the impact of digital change on European SMEs' business activities.     

风险投资如何助力中国科技创新

科技创新离不开金融支持。无论是基础研究还是技术转化都需要大量的资金支持,但早期研发成果市场化的失败率较高,与传统金融体系的风险偏好并不匹配,而风险投资对满足这方面资金需求发挥着重要作用,并起到价值发现、引导研发方向等作用。近年来,我国风险投资发展迅速,但风险投资体系仍有待完善。文章对全球具有代表性的美国、欧洲、日本和新加坡的风投模式进行比较分析,发现国有资本和民间资本的有效整合可以构建更为完整的风投体系。我国国有资本与民间资本各有优势,但未能在实践中形成合力,导致对科技创新的支持力度不足、企业资金需求与风险资本资金供给周期不匹配等问题。因此,未来的改革重点是要推进国有资本和民间资本的有效整合,逐步建立一个针对科技企业全生命周期、具有高度开放性和包容性的中国版本风投体系。     

Disturbance rejection using fuzzy model free adaptive control (FMFAC) with adaptive conditional defuzzification threshold

Disturbance rejection in nonlinear uncertain systems is a challenging issue especially when the sensor noise cannot be eliminated by low pass filtering. Fuzzy relational models (FRM) can effectively represent the sensor noise in the fuzzy control signal. Due to the large amount of sensor noise there will be huge actuator movement. In most of the cases the actuator movement is in response to the noise and not due to the set-point change. Conditional defuzzification is employed to reduce the control activity. The amount of control activity depends on the threshold level of the conditional defuzzification scheme. A novel scheme has been presented in this paper which can significantly reduce the actuator movement due to noise by adapting the conditional defuzzification threshold. Effective disturbance rejection can be achieved if the controller is modeled as an exact inverse of the plant model. The controller is a fuzzy relational model which develops the inverse plant model by incorporating feedback error learning. Sensitivity analyses have been carried out which demonstrate the efficiency of the proposed methodology.     

员工帮助计划(EAP):一种新兴的心理咨询模式和基于心理学的人力资源管理模式

从员工帮助计划(EAP)的含义、起源与发展、具体实施及作用效益等方面介绍了这一新兴的心理咨询模式和基于心理学的人力资源管理模式，提出了EAP的四级服务体系，探讨了EAP在中国存在的必要性和服务于中国的可能性。     

Cylinder position control driven by pneumatic digital bridge circuit using a fuzzy algorithm under large stroke and varying load conditions

A digital bridge circuit based on the concept of independent metering control can enable the precise position control of a pneumatic cylinder, but large strokes and variable loads still cause challenges. To solve this problem, a piecewise on/off valve flow compensator and a composite friction observer were innovatively designed in this study, and they were combined with a multiple fuzzy intelligent algorithm to ensure the accuracy and robustness of pneumatic position control. Considering the starting and stopping delays and the response processes of on/off valves, a six-stage flow–duty ratio linearization relationship was proposed. Employing a parameter identification method, a static and dynamic composite friction model was presented. Then, a fuzzy PID controller was proposed, and a genetic algorithm was used to optimize the control parameters. Experiment results showed that, when focusing on a large stroke (250 mm) and varying loads (8.5–18.5 kg), for sinusoidal signal with amplitude of 150 mm and frequency of 0.125 Hz and the air supply pressure is 0.5 Mpa, the algorithm in this study could ensure that the steady-state step response error was less than 1% and the root mean squared error of the sinusoidal trajectory tracking was less than 3%.     

Users’ evaluation of digital libraries (DLs): Their uses,their criteria,and their assessment

Millions of dollars have been invested into the development of digital libraries. There are many unanswered questions regarding their evaluation, in particular, from users’ perspectives. This study intends to investigate users’ use, their criteria and their evaluation of the two selected digital libraries. Nineteen subjects were recruited to participate in the study. They were instructed to keep a diary for their use of the two digital libraries, rate the importance of digital library evaluation criteria, and evaluate the two digital libraries by applying their perceived important criteria. The results show patterns of users’ use of digital libraries, their perceived important evaluation criteria, and the positive and negative aspects of digital libraries. Finally, the relationships between perceived importance of digital library evaluation criteria and actual evaluation of digital libraries and the relationships between use of digital libraries and evaluation of digital libraries as well as users’ preference, experience and knowledge structure on digital library evaluation are further discussed.     

Exploiting context-awareness and multi-criteria decision making to improve items recommendation using a tripartite graph-based model

Integrating useful input information is essential to provide efficient recommendations to users. In this work, we focus on improving items ratings prediction by merging both multiple contexts and multiple criteria based research directions which were addressed separately in most existent literature. Throughout this article, Criteria refer to the items attributes, while Context denotes the circumstances in which the user uses an item. Our goal is to capture more fine grained preferences to improve items recommendation quality using users’ multiple criteria ratings under specific contextual situations. Therefore, we examine the recommenders’ data from the graph theory based perspective by representing three types of entities (users, contextual situations and criteria) as well as their relationships as a tripartite graph. Upon the assumption that contextually similar users tend to have similar interests for similar item criteria, we perform a high-order co-clustering on the tripartite graph for simultaneously partitioning the graph entities representing users in similar contextual situations and their evaluated item criteria. To predict cluster-based multi-criteria ratings, we introduce an improved rating prediction method that considers the dependency between users and their contextual situations, and also takes into account the correlation between criteria in the prediction process. The predicted multi-criteria ratings are finally aggregated into a single representative output corresponding to an overall item rating. To guide our investigation, we create a research hypothesis to provide insights about the tripartite graph partitioning and design clear and justified preliminary experiments including quantitative and qualitative analyzes to validate it. Further thorough experiments on the two available context-aware multi-criteria datasets, TripAdvisor and Educational, demonstrate that our proposal exhibits substantial improvements over alternative recommendations approaches.     

Position control of Stewart manipulator using a new extended adaptive fuzzy sliding mode controller and observer (E-AFSMCO)

Previously proposed adaptive fuzzy sliding mode control (AFSMC) and adaptive fuzzy sliding mode observer (AFSMO) methods are mixed and extended for the case of affine systems in which the input gain matrix is state-dependent, non-diagonal and non-positive definite. The proposed Extended AFSMCO (E-AFSMCO) method is then applied for position control of a Stewart Manipulator (SM), whose parameters are strongly state-dependent and complex and not suitable for practical control purposes. A robust observer-based control method which can work with a simplified model of the plant, and at the same time can preserve the stability and performance of the overall complex system is of great need. In this study, the SM dynamic model is simplified by removing the dynamic effects of the legs and the neglected terms are considered as un-modeled dynamics, for which the upper bound of the uncertainty is progressively estimated using the proposed adaptation rules. The final controller is comprised of a fuzzy controller in parallel with a robust switching controller. The second Lyapunov theorem is used to prove the closed-loop asymptotic stability. The proposed E-AFSMCO method is verified numerically and experimentally, depicting the effectiveness of the method for real-time industrial applications.