Jose Emilio Labra-Gayo

Towards a journalist-based news recommendation system: The Wesomender approach

The present paper introduces a context-aware recommendation system for journalists to enable the identification of similar topics across different sources. More specifically a journalist-based recommendation system that can be automatically configured is presented to exploit news according to expert preferences. News contextual features are also taken into account due to the their special nature: time, current user interests, location or existing trends are combined with traditional recommendation techniques to provide an adaptive framework that deals with heterogeneous data providing an enhanced collaborative filtering system. Since the Wesomender approach is able to generate context-aware recommendations in the journalism field, a quantitative evaluation with the aim of comparing Wesomender results with the expectations of a team of experts is also performed to show that a context-aware adaptive recommendation engine can fulfil the needs of journalists daily work when retrieving timely and primary information is required.

SeDeLo: Using Semantics and Description Logics to Support Aided Clinical Diagnosis

Automated medical diagnosis systems based on knowledge-oriented descriptions have gained momentum with the emergence of semantic descriptions. The objective of this paper is to propose a normalized design that solves some of the problems which have been detected by authors in previous tools. The authors bring together two different technologies to develop a new clinical decision support system: description logics aimed at developing inference systems to improve decision support for the prevention, treatment and management of illness and semantic technologies. Because of its new design, the system is capable of obtaining improved diagnostics compared with previous efforts. However, this evaluation is more focused in the computational performance, giving as result that description logics is a good solution with small data sets. In this paper, we provide a well-structured ontology for automated diagnosis in the medical field and a three-fold formalization based on Description Logics with the use of Semantic Web technologies.

New trends on e-Procurement applying semantic technologies: Current status and future challenges

Abstract The present paper introduces and reviews existing technology and research works in the field of e-Procurement. More specifically this survey aims to collect those relevant approaches that have tackled the challenge of delivering more advanced and intelligent e-Procurement management systems due to its relevance in the industry to afford more timely, adaptable and flexible decisions in purchasing processes. Although existing tools and techniques have demonstrated their ability to manage e-Procurement processes as a part of a supply management system there is a lack of interoperability among tools, tangled dependencies between processes or difficulties to exploit existing data and information to name a few that are preventing a proper use of the new dynamic and data-based environment. On the other hand semantic-based technologies emerge to provide the adequate building blocks to represent domain-knowledge and elevate the meaning of information resources through a common and shared data model (RDF) with a formal query language (SPARQL) and accessible via the Internet Protocols. In this sense the Linked Data effort has gained momentum to apply the principles of the aforementioned initiative to boost the re-use of information and data across different tools and processes. That is why authors review both existing open issues in the context e-Procurement with special focus on public procurement and semantic-based approaches to address them. To do so a preliminary research study is conducted to assess the state of the art in the context of e-Procurement and semantic-based systems. Afterwards main drawbacks of existing e-Procurement systems are presented to narrow down in semantic-based approaches applied to this field. Once the current status in both areas is reviewed, authors purpose the use and creation of an e-Procurement index to evaluate the quality of service of procurement systems. In this light the Analytical Hierarchy Process (AHP) method is used to set up an initial weight for each indicator in the index and to perform a first comparison between traditional and semantic-based approaches. Finally some discussion, conclusions and future challenges are also outlined.

Empowering the access to public procurement opportunities by means of linking controlled vocabularies. A case study of Product Scheme Classifications in the European e-Procurement sector

The present paper introduces a method to promote existing controlled vocabularies to the Linked Data initiative. A common data model and an enclosed conversion method for knowledge organization systems based on semantic web technologies and vocabularies such as SKOS are presented. This method is applied to well-known taxonomies and controlled vocabularies in the business sector, more specifically to Product Scheme Classifications created by governmental institutions such as the European Union or the United Nations. Since these product schemes are available in a common and shared data model, the needs of the European e-Procurement sector are outlined to finally demonstrate how Linked Data can address some of the challenges for publishing and retrieving information resources. As a consequence, two experiments are also provided in order to validate the gain, in terms of expressivity, and the exploitation of this emerging approach to help both expert and end-users to make decisions on the selection of descriptors for public procurement notices.

New trends on e-Procurement applying semantic technologies

Abstract The present editorial note introduces the concept of e-Procurement and the use of semantic technologies to improve some of the processes involved in electronic purchasing processes. Currently there is a growing interest to boost the use of electronic communications to deal with Business-to-Business (B2B), Business-to-Consumer (B2C) or Administration-to-Administration (A2A) relationships. New technologies are emerging with the aim of: (1) reducing costs; (2) providing more intelligent environments to make decisions in more timely and accurate fashion and (3) improving the overall efficiency of business processes. More specifically, e-Procurement defined as the business to business purchase and sale of supplies over the Internet can be found in a variety of ways from public marketplaces involving many firms to private exchanges that are currently facing a challenging environment to migrate from paper-based systems to an electronic ecosystem. However several interlinked challenges to achieve a successful transition have been identified such as lack of interoperable and standard-based infrastructures (data and services), legal uncertainties including the necessity of improving trust, privacy and provenance of data and information and lack of transparency, accessibility or usability to name a few. In this context semantic-based technologies arise to afford a common and standard data model that eases the interoperability, integration and creation of knowledge-based systems. Taking into account the necessity of a more interoperable and intelligent system to manage e-Procurement processes and the emerging application of semantics in different domains, this special issue is intended to provide researchers, developers and practitioners a summary of the current status of e-Procurement applying semantics.

Leveraging Semantics to Represent and Compute Quantitative Indexes: The RDFIndex Approach

The compilation of key performance indicators (KPIs) in just one value is becoming a challenging task in certain domains to summarize data and information. In this context, policymakers are continuously gathering and analyzing statistical data with the aim of providing objective measures about a specific policy, activity, product or service and making some kind of decision. Nevertheless existing tools and techniques based on traditional processes are preventing a proper use of the new dynamic and data environment avoiding more timely, adaptable and flexible (on-demand) quantitative index creation. On the other hand, semantic-based technologies emerge to provide the adequate building blocks to represent domain-knowledge and process data in a flexible fashion using a common and shared data model. That is why a RDF vocabulary designed on the top of the RDF Data Cube Vocabulary to model quantitative indexes is introduced in this paper. Moreover a Java and SPARQL based processor of this vocabulary is also presented as a tool to exploit the index meta-data structure and automatically perform the computation process to populate new values. Finally some discussion, conclusions and future work are also outlined.

Identifying potential suppliers for competitive bidding using Latent Semantic Analysis

Chilecompra is the Chilean governmental agency in charge of Chiles Public Procurement System. One of its main current problems is that around 54% (supply indicator) of the public procurements that are submitted get less than three bids, which is the minimum required so that the procurement process may be free of technical, legal and ethical questionings. This article presents a method based on Natural Language Processing and Semantic Analysis in order to automatically identify prospective bidding candidates from a historical application dataset with a software tool which implements this method. The results are proven by using a dataset of procurement data and historical applications, biddings and adjudications of the suppliers. We compared the number of suppliers that applied for a tender and the number of prospective bidders identified by this method, and the domain procurement experts proved that the identified bidders were relevant to the new procurement.