NLSC: Unrestricted Natural Language-based Service Composition through Sentence Embeddings

Current approaches for service composition (assemblies of atomic services) require developers to use: (a) domain-specific semantics to formalize services that restrict the vocabulary for their descriptions, and (b) translation mechanisms for service retrieval to convert unstructured user requests to strongly-typed semantic representations. In our work, we argue that effort to developing service descriptions, request translations, and matching mechanisms could be reduced using unrestricted natural language; allowing both: (1) end-users to intuitively express their needs using natural language, and (2) service developers to develop services without relying on syntactic/semantic description languages. Although there are some natural language-based service composition approaches, they restrict service retrieval to syntactic/semantic matching. With recent developments in Machine learning and Natural Language Processing, we motivate the use of Sentence Embeddings by leveraging richer semantic representations of sentences for service description, matching and retrieval. Experimental results show that service composition development effort may be reduced by more than 44\% while keeping a high precision/recall when matching high-level user requests with low-level service method invocations.Comment: This paper will appear on SCC'19 (IEEE International Conference on Services Computing) on July 1

Staging Transformations for Multimodal Web Interaction Management

Multimodal interfaces are becoming increasingly ubiquitous with the advent of mobile devices, accessibility considerations, and novel software technologies that combine diverse interaction media. In addition to improving access and delivery capabilities, such interfaces enable flexible and personalized dialogs with websites, much like a conversation between humans. In this paper, we present a software framework for multimodal web interaction management that supports mixed-initiative dialogs between users and websites. A mixed-initiative dialog is one where the user and the website take turns changing the flow of interaction. The framework supports the functional specification and realization of such dialogs using staging transformations -- a theory for representing and reasoning about dialogs based on partial input. It supports multiple interaction interfaces, and offers sessioning, caching, and co-ordination functions through the use of an interaction manager. Two case studies are presented to illustrate the promise of this approach.Comment: Describes framework and software architecture for multimodal web interaction managemen

Learning Services Based on Formal Concept Reasoning

A formal foundation of automated service discovering for Semantic Web is proposed. The approach is based on the formalization of the problem using an agent oriented programming language (ConGolog), as well as on the use of the Formal Concept Analysis as a tool for knowledge extraction.Ministerio de Educación y Ciencia TIN 2004- 0388

A global database for metacommunity ecology, integrating species, traits, environment and space

The use of functional information in the form of species traits plays an important role in explaining biodiversity patterns and responses to environmental changes. Although relationships between species composition, their traits, and the environment have been extensively studied on a case-by-case basis, results are variable, and it remains unclear how generalizable these relationships are across ecosystems, taxa and spatial scales. To address this gap, we collated 80 datasets from trait-based studies into a global database for metaCommunity Ecology: Species, Traits, Environment and Space; “CESTES”. Each dataset includes four matrices: species community abundances or presences/absences across multiple sites, species trait information, environmental variables and spatial coordinates of the sampling sites. The CESTES database is a live database: it will be maintained and expanded in the future as new datasets become available. By its harmonized structure, and the diversity of ecosystem types, taxonomic groups, and spatial scales it covers, the CESTES database provides an important opportunity for synthetic trait-based research in community ecology

Induction trees for automatic word classification

This work studies induction tree application for certain word category detection by simple morpho-syntactical descriptors that are proposed here. The classification power for these new descriptors with and without stemming is also studied. Finally, results show that classification prediction power is good when stem is coordinated with a short list of descriptors.En este trabajo estudia el uso de árboles de inducción para la detección de ciertos tipos de palabras usando algunos descriptores morfosintáctico propuestos. También se estudia el poder de clasificación de estos nuevos descriptores con y sin extracción de raíces de palabras (stemming). Finalmente, se muestra en los resultados que el poder de predicción de la clasificación es bueno cuando se combinan stemming con algunos de los descriptores presentados.Red de Universidades con Carreras en Informática (RedUNCI

Temporal Data Modeling and Reasoning for Information Systems

Temporal knowledge representation and reasoning is a major research field in Artificial Intelligence, in Database Systems, and in Web and Semantic Web research. The ability to model and process time and calendar data is essential for many applications like appointment scheduling, planning, Web services, temporal and active database systems, adaptive Web applications, and mobile computing applications. This article aims at three complementary goals. First, to provide with a general background in temporal data modeling and reasoning approaches. Second, to serve as an orientation guide for further specific reading. Third, to point to new application fields and research perspectives on temporal knowledge representation and reasoning in the Web and Semantic Web

Simplification of Health and Social Services Enrollment and Eligibility: Lessons for California From Interviews in Four States

Explores state officials' and advocates' views on issues involved in streamlining enrollment and eligibility processes, including the importance of staff buy-in, community partners' outreach efforts, and technological challenges and lessons learned

Implementing means-tested welfare systems in the United States

While targeting can effectively channel resources to the poor, implementation details matter tremendously to distributive outcomes. Several key factors affect performance, including: data collection processes; information management; household assessment mechanisms; institutional arrangements; and monitoring and oversight mechanisms. This report conducts an in-depth assessment of key design and implementation factors and their potential impact on outcomes for the household targeting system used in the United States to target social programs to the poor and vulnerable.

05081 Abstracts Collection -- Foundations of Global Computing

From 20.02.05 to 25.02.05, the Dagstuhl Seminar 05081 on ``Foundations of Global Computing\u27\u27 was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available