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Competitive success as a nation requires balancing commercial innovativeness and social welfare, which results in a sound basis for socio‐economic development. All potential resources – including entrepreneurial activity and innovations – can be utilized as promoters of competitiveness and welfare. Thus, useful lessons for general national competitiveness can be learned from benchmarking individual innovations and perhaps even more so, from those less glamorized technologies such as human language technologies (HLT). Finnish researchers are considered to be at the leading edge of developments in a number of ICT fields. The main responsibility for the utilization of knowledge is seen, necessarily, to rest with the public sector, while the legislative framework is considered to favour entrepreneurship and innovation. Aims to discuss the issues.

National competitiveness and HLT benchmarking pose a number of interesting questions and issues both macro and micro levels. For example: the extent to which benchmark performance in HLT is consistent with national competitiveness; link between robustness of research effort in any particular language community and effectiveness of technology transfer to market; and fostering and funding of entrepreneurial activity in HLT in the successful (benchmarked) countries and the fit with national vision and innovation policy. For the first two areas, relationships between HLT benchmark and comparative national competitiveness of top countries are examined through comparison of their respective primitive dimensions. Data sources include official and quasi‐official public documents. The final stage is explored using a case study approach and comparative assessment against extant entrepreneurship literature.

There appears to be no direct link between robustness of the HLT research effort in any particular language community and actual effectiveness of technology transfer to market. None the less, success in the Finnish HLT benchmark appears to correlate with the country's international competitiveness standing and “social innovation policy” paradigm. Its knowledge society model has clearly resulted in a sound basis for its socio‐economic development, where all potential resources – including its entrepreneurial base – and innovations, can be utilized as promoters of competitiveness and welfare. Within this entrepreneurial base, HLT SMEs tend to seek scale economies through internationalise at the early stages of development.

The paper shows that Finland is well placed to meet the challenges and to capitalise on the economic and social opportunities, given its strength in ICT/HLT innovation policy country's open self‐criticism of the latter.

Conversational agents are natural language interaction interfaces designed to simulate conversation with a real person. This paper seeks to investigate current development and applications of these systems worldwide, while focusing on their availability in Canadian libraries. It aims to argue that it is both timely and conceivable for Canadian libraries to consider adopting conversational agents to enhance – not replace – face‐to‐face human interaction. Potential users include library web site tour guides, automated virtual reference and readers' advisory librarians, and virtual story‐tellers. To provide background and justification for this argument, the paper seeks to review agents from classic implementations to state‐of‐the‐art prototypes: how they interact with users, produce language, and control conversational behaviors.

The web sites of the 20 largest Canadian libraries were surveyed to assess the extent to which specific language‐related technologies are offered in Canada, including conversational agents. An exemplified taxonomy of four pragmatic purposes that conversational agents currently serve outside libraries – educational, informational, assistive, and socially interactive – is proposed and translated into library settings.

As of early 2010, artificially intelligent conversational systems have been found to be virtually non‐existent in Canadian libraries, while other innovative technologies proliferate (e.g. social media tools). These findings motivate the need for a broader awareness and discussion within the LIS community of these systems' applicability and potential for library purposes.

This paper is intended for reflective information professionals who seek a greater understanding of the issues related to adopting conversational agents in libraries, as this topic is scarcely covered in the LIS literature. The pros and cons are discussed, and insights offered into perceptions of intelligence (artificial or not) as well as the fundamentally social nature of human‐computer interaction.

This paper aims to develop a system, which would enable efficient management and exploitation of documentation in electronic form, related to mining projects, with information retrieval and information extraction (IE) features, using various language resources and natural language processing.

The system is designed to integrate textual, lexical, semantic and terminological resources, enabling advanced document search and extraction of information. These resources are integrated with a set of Web services and applications, for different user profiles and use-cases.

The use of the system is illustrated by examples demonstrating keyword search supported by Web query expansion services, search based on regular expressions, corpus search based on local grammars, followed by extraction of information based on this search and finally, search with lexical masks using domain and semantic markers.

The presented system is the first software solution for implementation of human language technology in management of documentation from the mining engineering domain, but it is also applicable to other engineering and non-engineering domains. The system is independent of the type of alphabet (Cyrillic and Latin), which makes it applicable to other languages of the Balkan region related to Serbian, and its support for morphological dictionaries can be applied in most morphologically complex languages, such as Slavic languages. Significant search improvements and the efficiency of IE are based on semantic networks and terminology dictionaries, with the support of local grammars.

The aim of this paper is to show how multilinguality is permanently present in organizations in this global world, and how they should take into account the multilingual phenomenon specifically from the perspective of knowledge management in order to gain presence in markets.

The approach followed by the authors consists of a review of the published literature addressing this issue during the last years, followed by a proposal of applicable technologies in each step of the information processing.

The clearest finding is that if technology is not used for solving the problems that arise when dealing with multilingual contents, efficient information managing turns out a rather difficult task.

The paper points out a number of different states in the information flows, which make it possible to study and analyse the most appropriate technologies for their orderly treatment. A unified treatment of the information flows is recommended, especially if there are multilingual components.

The issue of multilinguality in organizations, a possible cause of a weak penetration in the global world, has been scarcely studied and hardly tackled from a methodological perspective. This paper suggests technologies adequate for different situations when managing organizational information.

Seeks to explore the gap that exists between knowledge management (KM) systems and the natural language materials that form almost all corporate data stores.

A conceptual discussion and approach are taken using recent scientific results in the fields of the semantic web and ontology‐based information extraction.

Provides a high‐level introduction to information extraction (IE) and descriptions of application scenarios for KM tools that exploit IE, a form of natural language analysis to link semantic web models with documents. The paper presents some examples of ontology‐based IE systems, one of which, KIM, is under development in the SEKT Project. KIM offers IE‐based facilities for metadata creation, storage and conceptual search. The system can be used by diverse applications for annotating and querying documents.

Focuses on technologies and facilities that will become an important part of next‐generation KM applications.

In this paper we give a synoptic view of the growth of the text processing technology of information extraction (IE) whose function is to extract information about a pre‐specified set of entities, relations or events from natural language texts and to record this information in structured representations called templates. Here we describe the nature of the IE task, review the history of the area from its origins in AI work in the 1960s and 70s till the present, discuss the techniques being used to carry out the task, describe application areas where IE systems are or are about to be at work, and conclude with a discussion of the challenges facing the area. What emerges is a picture of an exciting new text processing technology with a host of new applications, both on its own and in conjunction with other technologies, such as information retrieval, machine translation and data mining.

The purpose of this paper is to treat disinformation and misinformation (intentionally deceptive and unintentionally inaccurate misleading information, respectively) as a socio-cultural technology-enabled epidemic in digital news, propagated via social media.

The proposed disinformation and misinformation triangle is a conceptual model that identifies the three minimal causal factors occurring simultaneously to facilitate the spread of the epidemic at the societal level.

Following the epidemiological disease triangle model, the three interacting causal factors are translated into the digital news context: the virulent pathogens are falsifications, clickbait, satirical “fakes” and other deceptive or misleading news content; the susceptible hosts are information-overloaded, time-pressed news readers lacking media literacy skills; and the conducive environments are polluted poorly regulated social media platforms that propagate and encourage the spread of various “fakes.”

The three types of interventions – automation, education and regulation – are proposed as a set of holistic measures to reveal, and potentially control, predict and prevent further proliferation of the epidemic. Partial automated solutions with natural language processing, machine learning and various automated detection techniques are currently available, as exemplified here briefly. Automated solutions assist (but not replace) human judgments about whether news is truthful and credible. Information literacy efforts require further in-depth understanding of the phenomenon and interdisciplinary collaboration outside of the traditional library and information science, incorporating media studies, journalism, interpersonal psychology and communication perspectives.

This paper sets out to discuss the use of information extraction (IE), a natural language‐processing (NLP) technique to assist “rich” semantic indexing of diverse archaeological text resources. The focus of the research is to direct a semantic‐aware “rich” indexing of diverse natural language resources with properties capable of satisfying information retrieval from online publications and datasets associated with the Semantic Technologies for Archaeological Resources (STAR) project.

The paper proposes use of the English Heritage extension (CRM‐EH) of the standard core ontology in cultural heritage, CIDOC CRM, and exploitation of domain thesauri resources for driving and enhancing an Ontology‐Oriented Information Extraction process. The process of semantic indexing is based on a rule‐based Information Extraction technique, which is facilitated by the General Architecture of Text Engineering (GATE) toolkit and expressed by Java Annotation Pattern Engine (JAPE) rules.

Initial results suggest that the combination of information extraction with knowledge resources and standard conceptual models is capable of supporting semantic‐aware term indexing. Additional efforts are required for further exploitation of the technique and adoption of formal evaluation methods for assessing the performance of the method in measurable terms.

The value of the paper lies in the semantic indexing of 535 unpublished online documents often referred to as “Grey Literature”, from the Archaeological Data Service OASIS corpus (Online AccesS to the Index of archaeological investigationS), with respect to the CRM ontological concepts E49.Time Appellation and P19.Physical Object.

Computer‐assisted language learning (CALL) comes in many different flavors. The purpose of this paper is to focus on developing an integrated e‐learning environment that allows improving language skills in specific contexts. Integrated e‐learning environment means that it is a web‐based solution that performs language learning tasks using common working environments such as, for instance, web browsers or e‐mail clients. It should be accessible on different platforms, even on mobile devices. Natural language processing (NLP) forms the technological basis for developing such a learning framework. The use of NLP technologies, or in broader view artificial intelligence technologies, in CALL has also been dubbed intelligent CALL. The paper gives an overview of the state of the art in this area.

On the one hand, the paper explains creation processes for NLP resources and gives an overview of language corpora. On the other hand, it describes existing NLP standards. Based on the authors' requirements, the paper gives special attention to the evaluation and comparison of toolkits that can suitably support the planned implementation. In consideration of the evaluation results, the authors give a closer look at the system architecture of the CALL platform. An outlook at the end points out necessary developments in e‐learning to keep in mind.

Based on evaluation result, the authors have designed the framework architecture for the intelligent integrated CALL (iiCALL) system. A first prototype shows a web browser plug‐in communicating with the framework started in an Apache Tomcat server environment.

The paper presents an extended version of a paper that has been selected as one of the invited papers for journal special issue consideration at iiWAS2010. It focuses on the evaluation of several NLP toolkits which might be of importance for those who plan to integrate NLP technologies in their projects.

The paper shows how access to knowledge can be enhanced by using a set of innovative approaches and technologies based on the semantic web.

Emerging trends in knowledge access are considered followed by a description of how ontologies and semantics can contribute. A set of tools is then presented which is based on semantic web technology. For each of these tools a detailed description of the approach is given together with an analysis of related and future work as appropriate.

The tools presented are at the prototype stage but can already show how knowledge access can be improved by allowing users to more precisely express what they are looking for and by presenting to them in a form that is appropriate to their current context.

The tools show promising results in improving access to knowledge which will be further evaluated within a practical setting. The tools will be integrated and trialled as part of case studies within the SEKT project. This will allow their usability and practical applicability to be measured.

Ontologies as a form of knowledge representation are increasing in importance. Knowledge management, and in particular knowledge access, will benefit from their widespread acceptance. The use of open standards and compatible tools in this area will be important to support interoperability and widespread access to disparate knowledge repositories.

The paper presents research in an emerging but increasingly important field, i.e. semantic web‐based knowledge technology. It describes how this technology can satisfy the demand for improved knowledge access, including providing knowledge delivery to users at the right time and in the correct form.