Towards a unified framework for opinion retrieval, mining and summarization

The exponential increase of subjective, user-generated content since the birth of the Social Web, has led to the necessity of developing automatic text processing systems able to extract, process and present relevant knowledge. In this paper, we tackle the Opinion Retrieval, Mining and Summarization task, by proposing a unified framework, composed of three crucial components (information retrieval, opinion mining and text summarization) that allow the retrieval, classification and summarization of subjective information. An extensive analysis is conducted, where different configurations of the framework are suggested and analyzed, in order to determine which is the best one, and under which conditions. The evaluation carried out and the results obtained show the appropriateness of the individual components, as well as the framework as a whole. By achieving an improvement over 10% compared to the state-of-the-art approaches in the context of blogs, we can conclude that subjective text can be efficiently dealt with by means of our proposed framework.     

A VNS heuristic for escaping local extrema entrapment in normalized cut clustering

Normalized cut is one of the most popular graph clustering criteria. The main approaches proposed for its resolution are spectral clustering methods and a multilevel approach of Dhillon et al. (TPAMI 29:1944–1957, 2007), called graclus. Their aim is to obtain good solutions in a small amount of time for large instances. Metaheuristics are general frameworks for stochastic searches often employed in global optimization to improve the solutions obtained by other heuristics. Variable neighborhood search (VNS) is a metaheuristic which exploits systematically the idea of neighborhood change during the search. In this paper, we propose a VNS heuristic for normalized cut segmentation. Computational experiments show that in most cases this VNS heuristic improves significantly, and in moderate time, the solutions obtained by the current state-of-the-art algorithms, i.e., graclus and a spectral method proposed by Yu and Shi (ICCV, 2003).     

Segmentation of cervical cell nuclei in high-resolution microscopic images: A new algorithm and a web-based software framework

In order to automate cervical cancer screening tests, one of the most important and longstanding challenges is the segmentation of cell nuclei in the stained specimens. Though nuclei of isolated cells in high-quality acquisitions often are easy to segment, the problem lies in the segmentation of large numbers of nuclei with various characteristics under differing acquisition conditions in high-resolution scans of the complete microscope slides. We implemented a system that enables processing of full resolution images, and proposes a new algorithm for segmenting the nuclei under adequate control of the expert user. The system can work automatically or interactively guided, to allow for segmentation within the whole range of slide and image characteristics. It facilitates data storage and interaction of technical and medical experts, especially with its web-based architecture. The proposed algorithm localizes cell nuclei using a voting scheme and prior knowledge, before it determines the exact shape of the nuclei by means of an elastic segmentation algorithm. After noise removal with a mean-shift and a median filtering takes place, edges are extracted with a Canny edge detection algorithm. Motivated by the observation that cell nuclei are surrounded by cytoplasm and their shape is roughly elliptical, edges adjacent to the background are removed. A randomized Hough transform for ellipses finds candidate nuclei, which are then processed by a level set algorithm. The algorithm is tested and compared to other algorithms on a database containing 207 images acquired from two different microscope slides, with promising results.     

A platform for the development of patient applications in the domain of personalized health

Personalized health (p-health) systems can contribute significantly to the sustainability of healthcare systems, though their feasibility is yet to be proven. One of the problems related to their development is the lack of well-established development tools for this domain. As the p-health paradigm is focused on patient self-management, big challenges arise around the design and implementation of patient systems. This paper presents a reference platform created for the development of these applications, and shows the advantages of its adoption in a complex project dealing with cardio-vascular diseases.     

Methodological design and comparative evaluation of a MAS providing AmI

Researches on Ambient Intelligent and Ubiquitous Computing using wireless technologies have increased in the last years. In this work, we review several scenarios to define a multi-agent architecture that support the information needs of these new technologies, for heterogeneous domain. Our contribution consists of designing in a methodological way a Context Aware System (involving location services) using agents that can be used in very different domains. We describe all the steps followed in the design of the agent system. We apply a hybridizing methodology between GAIA and AUML. Additionally we propose a way to compare different agent architectures for Context Aware System using agent interactions. So, in this paper, we describe the assignment of weight values to agents interaction in two different MAS architectures for Context Aware problems solving different scenarios inspired in FIPA standard negotiation protocols.     

Open Innovation in an Enterprise 3.0 framework: Three case studies

Nowadays, especially after the recent financial downturn, companies are looking for much more efficient and creative business processes. They need to place better solutions in the market in a less time with less cost. There is a general intuition that communication and collaboration, especially mixed with Web 2.0 approach within companies and ecosystems, can boost the innovation process with positive impacts on business indicators. Open Innovation within an Enterprise 2.0 context is a one of the most chosen paradigm for improving the innovation processes of enterprises, based on the collaborative creation and development of ideas and products. The key feature of this new paradigm is that the knowledge is exploited in a collaborative way flowing not only among internal sources, i.e. R&D departments, but also among external ones as other employees, customers, partners, etc. In this paper we show how an ontology-based analysis of plain text can provide a semantic contextualization of content support tasks, such as finding semantic distance between contents, and can help in creating relations between people with shared knowledge and interests. Along this paper we will present the results obtained by the adoption of this technology in a large corporate environment like Bankinter, a financial institution, Telefonica I+D, an international telecommunication firm and Repsol, a major oil company in Spain.     

A case based reasoning model for multilingual language generation in dialogues

The process of Natural Language Generation for a Conversational Agent translates some semantic language to its surface form expressed in natural language. In this paper, we are going to show a Case Based Reasoning technique which is easily extensible and adaptable to multiple domains and languages, that generates coherent phrases and produces a natural outcome in the context of a Conversational Agent that maintains a dialogue with the user.     

Petri net-based engine for adaptive learning

In this paper, an IMS LD engine based on a Petri net model that represents the operational semantics of units of learning based on this specification is presented. The Petri nets of this engine, which is called OPENET4LD, verify the structural properties that are desirable for a learning flow and also facilitate the adaptation of the engine if potential changes in the IMS LD specification were proposed. Furthermore, OPENET4LD has an open and flexible architecture based on a set of ontologies that describe both the semantics of the Petri nets execution and the semantics of each learning flow component of IMS LD. Furthermore, the implementation of this architecture has been exhaustively validated with a number of UoLs that are compliant with the levels A and B of IMS LD.     

Two‐phase thermo‐mechanical and macrosegregation modelling of binary alloys solidification with emphasis on the secondary cooling stage of steel slab continuous casting processes

As an approach towards a better modelling of solidification problems, we introduce a thermo‐mechanical and macrosegregation model that considers a solidifying alloy as a binary mixture made of a liquid and a solid phase. Macroscopic conservation laws for mass, momentum and solute are obtained by spatial averaging of the respective microscopic conservation equations. Assuming local thermal equilibrium, a single equation for the conservation of the mixture energy is then written. A single equation can be obtained for the solute as well by invoking a proper microsegregation rule. The numerical implementation in a two‐dimensional finite element code is then detailed. Lastly, some examples of simulations of academic tests as well as industrial applications for continuous casting of steel slabs are discussed. They particularly enlighten the ability of the formulation to describe the formation of central macrosegregation during the secondary cooling of slab continuous casting processes. Copyright © 2006 John Wiley & Sons, Ltd.     

Model of Precipitation Kinetics Induced by Strain for Microalloyed Steels

In microalloyed steels, static recrystallisation is temporarily inhibited by precipitation which is occurring at the same time. A high number of microalloyed steels containing various combinations of carbon, nitrogen and precipitate forming elements like V, Nb and Ti were recrystallised at different temperatures and strain rates. From these results recrystallisation‐precipitation–time‐temperature (RPTT) diagrams were established. The influence of grain size and strain rate on the RPTT diagrams was studied. The precipitation kinetics were mathematically described for isothermal conditions and converted to cooling conditions, which enables an application to hot rolling. Under cooling conditions, completion of recrystallisation is prevented, especially for Nb alloyed steels.