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This study aims to identify user perception of different qualities of optical character recognition (OCR) in texts. The purpose of this paper is to study the effect of different quality OCR on users' subjective perception through an interactive information retrieval task with a collection of one digitized historical Finnish newspaper.

This study is based on the simulated work task model used in interactive information retrieval. Thirty-two users made searches to an article collection of Finnish newspaper Uusi Suometar 1869–1918 which consists of ca. 1.45 million autosegmented articles. The article search database had two versions of each article with different quality OCR. Each user performed six pre-formulated and six self-formulated short queries and evaluated subjectively the top 10 results using a graded relevance scale of 0–3. Users were not informed about the OCR quality differences of the otherwise identical articles.

The main result of the study is that improved OCR quality affects subjective user perception of historical newspaper articles positively: higher relevance scores are given to better-quality texts.

To the best of the authors’ knowledge, this simulated interactive work task experiment is the first one showing empirically that users' subjective relevance assessments are affected by a change in the quality of an optically read text.

Data protection requirements heavily increased due to the rising awareness of data security, legal requirements and technological developments. Today, NoSQL databases are increasingly used in security-critical domains. Current survey works on databases and data security only consider authorization and access control in a very general way and do not regard most of today’s sophisticated requirements. Accordingly, the purpose of this paper is to discuss authorization and access control for relational and NoSQL database models in detail with respect to requirements and current state of the art.

This paper follows a systematic literature review approach to study authorization and access control for different database models. Starting with a research on survey works on authorization and access control in databases, the study continues with the identification and definition of advanced authorization and access control requirements, which are generally applicable to any database model. This paper then discusses and compares current database models based on these requirements.

As no survey works consider requirements for authorization and access control in different database models so far, the authors define their requirements. Furthermore, the authors discuss the current state of the art for the relational, key-value, column-oriented, document-based and graph database models in comparison to the defined requirements.

This paper focuses on authorization and access control for various database models, not concrete products. This paper identifies today’s sophisticated – yet general – requirements from the literature and compares them with research results and access control features of current products for the relational and NoSQL database models.

One of the main tasks of a researcher is to properly communicate the results he obtained. The choice of the journal in which to publish the work is therefore very important. However, not all journals have suitable characteristics for a correct dissemination of scientific knowledge. Some publishers turn out to be unreliable and, against a payment, they publish whatever researchers propose. The authors call “predatory journals” these untrustworthy journals. The purpose of this paper is to analyse the incidence of predatory journals in computer science literature and present a tool that was developed for this purpose.

The authors focused their attention on editors, universities and publishers that are involved in this kind of publishing process. The starting point of their research is the list of scholarly open-access publishers and open-access stand-alone journals created by Jeffrey Beall. Specifically, they analysed the presence of predatory journals in the search results obtained from Google Scholar in the engineering and computer science fields. They also studied the change over time of such incidence in the articles published between 2011 and 2015.

The analysis shows that the phenomenon of predatory journals somehow decreased in 2015, probably due to a greater awareness of the risks related to the reputation of the authors.

We focused on computer science field, using a specific sample of queries. We developed a software to automatically make queries to the search engine, and to detect predatory journals, using Beall’s list.

For companies that intend to respond to the modern conscious consumers' needs, a great competitive advantage is played on the ability to incorporate sustainability messages in marketing communications. The aim of this paper is to address this important priority in the web context, building a semantic algorithm that allows content managers to evaluate the quality of sustainability web contents for search engines, considering the current semantic web development.

Following the Design Science (DS) methodological approach, the study develops the algorithm as an artefact capable of solving a practical problem and improving the operation of content managerial process.

The algorithm considers multiple factors of evaluation, grouped in three parameters: completeness, clarity and consistency. An applicability test of the algorithm was conducted on a sample of web pages of the Google blog on sustainability to highlight the correspondence between the established evaluation factors and those actually used by Google.

Studying content marketing for sustainability communication constitutes a new field of research that offers exciting opportunities. Writing sustainability contents in an effective way is a fundamental step to trigger stakeholder engagement mechanisms online. It could be a positive social engineering technique in the hands of marketers to make web users able to pursue sustainable development in their choices.

This is the first study that creates a theoretical connection between digital content marketing and sustainability communication focussing, especially, on the aspects of search engine optimization (SEO). The algorithm of “Sustainability-contents SEO” is the first operational software tool, with a regulatory nature, that is able to analyse the web contents, detecting the terms of the sustainability language and measuring the compliance to SEO requirements.

In order to sustain the development and utilization of learning content under the limited financial and human resources, the sharing and reuse of open educational resources (OERs) have been promoted in various school levels and disciplines. In many countries, central organization(s) collect both learning content and its metadata, and provide them to learners and teachers with distinctive value‐added services from their portals. Collaborations among the national portals have also emerged beyond borders.Global Learning Object Brokered Exchange (GLOBE) is an international consortium of the hub organizations, which manage a federated repository and/or a meta‐referatory in each country and region. GLOBE was established in September 2004 by five founding members, and now twelve organizations in the world participate in. By adopting IEEE LOM version 1.0 for the metadata standards, SQI for the query language, and OAI‐PMH for harvesting, GLOBE realized a global search and delivery infrastructure for lifelong learning (LLL). At present, while the repositories all over the world store huge number of learning content and metadata, the variance of the quality becomes much bigger. In addition, because the effectiveness of learning content is relative and dependent on contextual factors, both optimizations specialized in learner characteristics and localizations to each language/culture are indispensable. The users need some supports on the quality and pedagogical guidance when they find their right content. GLOBE, based on multilingualism, multiculturalism and pluralism, collaborates to build up standardized services on the quality assurance of the content utilizing the “Educational” items of LOM. In AAOU framework also, the organizations can promote “openness”, and share the quality learning content and educational information by using a standardized content search and delivery infrastructure.

Enterprise knowledge graphs (EKG) in resource description framework (RDF) consolidate and semantically integrate heterogeneous data sources into a comprehensive dataspace. However, to make an external relational data source accessible through an EKG, an RDF view of the underlying relational database, called an RDB2RDF view, must be created. The RDB2RDF view should be materialized in situations where live access to the data source is not possible, or the data source imposes restrictions on the type of query forms and the number of results. In this case, a mechanism for maintaining the materialized view data up-to-date is also required. The purpose of this paper is to address the problem of the efficient maintenance of externally materialized RDB2RDF views.

This paper proposes a formal framework for the incremental maintenance of externally materialized RDB2RDF views, in which the server computes and publishes changesets, indicating the difference between the two states of the view. The EKG system can then download the changesets and synchronize the externally materialized view. The changesets are computed based solely on the update and the source database state and require no access to the content of the view.

The central result of this paper shows that changesets computed according to the formal framework correctly maintain the externally materialized RDB2RDF view. The experiments indicate that the proposed strategy supports live synchronization of large RDB2RDF views and that the time taken to compute the changesets with the proposed approach was almost three orders of magnitude smaller than partial rematerialization and three orders of magnitude smaller than full rematerialization.

The main idea that differentiates the proposed approach from previous work on incremental view maintenance is to explore the object-preserving property of typical RDB2RDF views so that the solution can deal with views with duplicates. The algorithms for the incremental maintenance of relational views with duplicates published in the literature require querying the materialized view data to precisely compute the changesets. By contrast, the approach proposed in this paper requires no access to view data. This is important when the view is maintained externally, because accessing a remote data source may be too slow.

This paper aims to make it convenient for those who have only just begun their research into Community Question Answering (CQA) expert recommendation, and for those who are already concerned with this issue, to ease the extension of our understanding with future research.

In this paper, keywords such as “CQA”, “Social Question Answering”, “expert recommendation”, “question routing” and “expert finding” are used to search major digital libraries. The final sample includes a list of 83 relevant articles authored in academia as well as industry that have been published from January 1, 2008 to March 1, 2019.

This study proposes a comprehensive framework to categorize extant studies into three broad areas of CQA expert recommendation research: understanding profile modeling, recommendation approaches and recommendation system impacts.

This paper focuses on discussing and sorting out the key research issues from these three research genres. Finally, it was found that conflicting and contradictory research results and research gaps in the existing research, and then put forward the urgent research topics.