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In recent years, readers have limited amounts of time to pick the right books to read from a market that is filled with similar types of books. Aiming to read only good books, readers tend to check book reviews written by others. However, it is very difficult to find good book reviews. The aim of this paper is to present a book review recommendation system that collects reviews from heterogeneous sources on the Internet and performs quality judgments automatically. Users can then read the top‐ranked reviews suggested by this recommendation system.

In this paper, a book review recommendation system is constructed to collect, process, and judge the quality of book reviews from various heterogeneous sources. The quality measurement of book reviews uses review‐evaluation techniques. The prediction results were validated with a ranking list produced by experts.

The proposed system is effective and suitable for recommending quality book reviews from heterogeneous sources. The proposed quality measurement method is more effective than other more commonly used methods.

This paper is one of the first to apply review evaluation techniques to the process of book review recommendation. The proposed system can collect and recognize book reviews from different websites with various forms of presentation. This evaluation shows that the quality measurement method produces better results than do other methods, such as ranking by rating score or by the date that the review was posted. Those methods are primarily used by commercial websites.

To identify cases related to design of ICT platforms for industrial alliances, where the use of Ontology‐driven architectures based on Semantic web standards is more advantageous than application of conventional modeling together with XML standards.

A comparative analysis of the two latest and the most obvious use cases (NASA and Nordic Process Industry Data Exchange Alliance) concerned with development of an environment for integration and collaboration of industrial partners, has been used as a basis for the research results. Additionally, dynamics of changes in a domain data model and their consequences have been analyzed on a couple of typical use cases.

Ontology‐driven architectures of a collaboration and integration ICT platforms have been recognized as more appropriate for a technical support of industrial alliances around a supply‐chains with a long life cycles.

More typical cases related to changes in domain data/knowledge models and to necessity of their integration, have to be considered and analyzed in search of advantageous of ontological modeling over conventional modeling approaches. Ways of a gradual change from conventional domain models to ontological ones in ICT systems have to be studied. The significance of existing XML‐based tools and the popularity of XML has to be estimated for the wide adoption of Semantic web principles.

The modeling approach which will be used as a core for building a collaboration and integration ICT platforms has to be carefully selected. Incorrect choice (e.g. UML together with XML) can cause consequences that will be hard to reform. The paper is anticipated to facilitate faster adoption of the Semantic web approach by industry.

The serious revision of existing and emerging domain modeling approaches has been undertaken. More unique arguments in favor of ontological modeling have been discovered. The paper is intended for serious consideration by emerging industrial alliances with regard to their choice in a core technology that will technically enable integration and collaboration between partners.

The paper's aim is to present a method for integrating high‐performance circuit components onto flexible substrates using self‐assembly. The basic process of self‐assembly at the micrometer‐scale is reviewed and recent work in building functional parts such as silicon transistors and compound semiconductor light emitting diodes, as well as their integration onto flexible plastic templates, is reported.

A micron‐scale self‐assembly method was used for building flexible circuits. In micron‐scale self‐assembly, functional micro‐components are independently microfabricated and subsequently allowed to self‐assemble on a template with electrical interconnects and corresponding binding sites in a fluid.

The self‐assembly process can achieve heterogeneous integration with a potentially very high yield. Successful assembly of functional micro‐components such as LEDs and transistors on plastic has been demonstrated.

The paper demonstrates fabrication techniques for free‐standing micro‐components with novel designs, low‐temperature fabrication on thin plastic sheets, and using capillary‐gravity‐based self‐assembly for the integration of crystalline inorganic semiconductor components onto unconventional substrates such as flexible polymers.

The traditional drug development process is costly, time consuming and risky. Using computational methods to discover drug repositioning opportunities is a promising and efficient strategy in the era of big data. The explosive growth of large-scale genomic, phenotypic data and all kinds of “omics” data brings opportunities for developing new computational drug repositioning methods based on big data. The paper aims to discuss this issue.

Here, a new computational strategy is proposed for inferring drug–disease associations from rich biomedical resources toward drug repositioning. First, the network embedding (NE) algorithm is adopted to learn the latent feature representation of drugs from multiple biomedical resources. Furthermore, on the basis of the latent vectors of drugs from the NE module, a binary support vector machine classifier is trained to divide unknown drug–disease pairs into positive and negative instances. Finally, this model is validated on a well-established drug–disease association data set with tenfold cross-validation.

This model obtains the performance of an area under the receiver operating characteristic curve of 90.3 percent, which is comparable to those of similar systems. The authors also analyze the performance of the model and validate its effect on predicting the new indications of old drugs.

This study shows that the authors’ method is predictive, identifying novel drug–disease interactions for drug discovery. The new feature learning methods also positively contribute to the heterogeneous data integration.

This paper aims to propose an integrating model for creating virtual libraries in Iranian universities of medical sciences.

This study was conducted with an analytic survey method. The statistical population comprised 66 Iranian universities of medical sciences, of which 59 libraries participated in the study. A researcher-made checklist was used for data collection. To ensure the accuracy of data, interviews and, in some cases, observations were also performed. Statistical estimates, including frequency, percentage, cumulative frequency and diagrams, were used for data analysis, and the system analysis method was used for modeling.

Results demonstrated that the library software programs of the studied universities of medical sciences do not have desirable interoperability capabilities. Only Azarsa program can exchange information with other systems. In terms of metadata and its standards, the studied libraries use programs with various standards, with MARC and Dublin Core standards being the most frequently used ones in the studied sample.

The model proposed here for integration is a hybrid model which can translate metadata standards and use the Z39.50 and OEI protocol to transfer data.

This paper investigates the latest achievements of studies on industrial information integration engineering (IIIE).

This paper extends the research by Chen (2016) by reviewing studies from 2016 to 2019 in IEEE Xplore and Web of Science. Altogether, 970 papers related to IIIE are grouped into 27 research categories and reviewed.

The results obtained in this study indicate that the number of research studies on IIIE rose drastically in the past three years compared with the findings in Chen (2016). Particularly, energy, engineering, industrial control, information and communications technologies, instrumentation, manufacturing and transportation are the hot topics. This change proves that the Internet of things (IoT) and IIIE have integrated closely by providing more applications, such as industrial Internet of things (IIoT), cyber-physical system (CPS), smart grids and smart manufacturing. This change also proves the research direction of IIIE identified by Chen (2016).

The results present up-to-date development of IIIE and provide directions for future research on IIIE. The review identifies that energy, engineering, industrial control, information and communications technologies, instrumentation, manufacturing and transportation are the main fields that most of the reviewed papers focus on. Applications that integrate IoT and IIIE, including IIoT, CPS, smart grids and smart manufacturing, are attracting scholars' and practitioners' attention. Some new technologies, such as 5G and blockchain, have the potential to be integrated with IoT and IIIE.

The purpose of this paper is to focus on through‐silicon via (TSV), with a new concept that every chip or interposer could have two surfaces with circuits. Emphasis is placed on the 3D IC integration, especially the interposer (both active and passive) technologies and their roadmaps. The origin of 3D integration is also briefly presented.

This design addresses the electronic packaging of 3D IC integration with a passive TSV interposer for high‐power, high‐performance, high pin‐count, ultra fine‐pitch, small real‐estate, and low‐cost applications. To achieve this, the design uses chip‐to‐chip interconnections through a passive TSV interposer in a 3D IC integration system‐in‐package (SiP) format with excellent thermal management.

A generic, low‐cost and thermal‐enhanced 3D IC integration SiP with a passive interposer has been proposed for high‐performance applications. Also, the origin of 3D integration and the overview and outlook of 3D Si integration and 3D IC integration have been presented and discussed. Some important results and recommendations are summarized: the TSV/redistribution layer (RDL)/integrated passive devices passive interposer, which supports the high‐power chips on top and low‐power chips at its bottom, is the gut and workhorse of the current 3D IC integration design; with the passive interposer, it is not necessary to “dig” holes on the active chips. In fact, try to avoid making TSVs in the active chips; the passive interposer provides flexible coupling for whatever chips are available and/or necessary, and enhances the functionality and possibly the routings (shorter); with the passive interposer, the TSV manufacturing cost is lower because the requirement of TSV manufacturing yield is too high (>99.99 percent) for the active chips to bear additional costs due to TSV manufacturing yield loss; with the passive interposer, wafer thinning and thin‐wafer handling costs (for the interposer) are lower because these are not needed for the active chips and thus adds no cost due to yield loss; with the current designs, all the chips are bare; the packaging cost for individual chips is eliminated; more than 90 percent of heat from the 3D IC integration SiP is dissipated from the backside of high‐power chips using a thermal interface material and heat spreader/sink; the appearance and footprint of current 3D IC integration SiP designs are very attractive to integrated device manufactures, original equipment manufactures, and electronics manufacturing services (EMS) because they are standard packages; and underfills between the copper‐filled TSV interposer and the high‐ and low‐power chips are recommended to reduce creep damage of the lead‐free microbump solder joints and prolong their lives.

The paper's findings will be very useful to the electronic industry.

Major objective of the instant study was to investigate the factors affecting the adoption of integrated semantic digital libraries (SDLs). It attempted to find out the challenges faced in implementing semantic technologies in digital libraries. This study also aimed to develop a framework to provide practical solutions to efficiently adopt semantic digital library systems to offer richer data and services.

To meet the formulated objectives of the study, a systematic literature review was conducted. The authors adhered to the “Preferred Reporting Items for the Systematic Review and Meta-analysis” (PRISMA) guidelines as a research method. The data were retrieved from different tools and databases. In total, 35 key studies were included for systematic review after having applied standard procedures.

The findings of the study indicated that SDLs are highly significant as they offered context-based information resources. Interoperability of the systems, advancement in bilateral transfer modules, machine-controlled indexing, and folksonomy were key factors in developing semantic digital libraries. The study identified five different types of challenges to build an integrated semantic digital library system. These challenges included ontologies and interoperability, development of a suitable model, diversity in language, lack of skilled human resources, and other technical issues.

This paper provided a framework that is based on practical solutions as a benchmark for policymakers to devise formal standards for the initiation to develop integrated semantic digital libraries.

This paper aims to investigate how value drivers of internet medical business model affect value creation through a configurational approach. The internet medical business model (IMBM) is such a business model that integrates online and offline medical services with the driving force of internet technologies covering prediagnosis, in-diagnosis and postdiagnosis. The outbreak of COVID-19 and the support of national policies have boosted the development of internet health care. However, there are still many challenges in practice, such as the unclear innovation path, as well as difficulties in landing and profiting. Academic research has not yet provided sufficient theoretical insights. Therefore, to better explain and guide practice, it is urgent to clarify the innovation path and mechanism of value creation for IMBM.

Based on the sample of 58 internet medical firms in China, this paper adopts fuzzy-set qualitative comparative analysis (fsQCA) to explore the configurational effects of IMBM’s value drivers on value creation.

Building on the business model canvas and the characteristics of internet health care, five value drivers of IMBM are identified, namely, functional value proposition, emotional value proposition, user involvement, resource capabilities and connection properties. And the five value drivers form three configurations, which are, respectively, labeled as resource-driven configuration, user-operated configuration and product-combined configuration. From the perspective of the integration of traditional and emerging theories, such as resource-based view, internet economics and value cocreation, each configuration leads to value creation and improves value results with different mechanisms behind it.

First, combined with the business model canvas and the characteristics of internet health care, this paper identifies five value drivers of IMBM, thus improving the relevant research on internet health care. Second, based on the configurational effects, this paper discusses the mechanism behind the configurational effects of IMBM’s value drivers on value creation, thus expanding relevant research on the value creation of business models. Third, applying fsQCA and combining the advantages of qualitative research and quantitative research, this paper adds to the configurations of IMBM’s value drivers that achieve high-value results.