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    1. Aspects and Multi-aspects

      This chapter starts with a discussion of how different aspects can be associated with the same entity and how this allows you to decompose a system in different ways. This leads to a consideration of the concept of multi-aspect which provides a uniform way to associate an unlimited number of related aspects with the same entity. Pruning a multi-aspect involves setting its multiplicity and restructuring it into an ordinary aspect with the specified number of components. We show how pruning of multi-aspects effectively open up a large space of simulation models with an unbounded variety of possibilities for coupling their ...
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    2. Intelligence in the Cloud

      We have seen how web and cloud technology allow us to easily store and process vast amounts of information, and as we saw in Chap. 6, there are many different data storage models used in the cloud. This chapter looks at how we can start to unlock the hidden potential of that data, to find the ‘golden nuggets’ of truly useful information contained in the overwhelming mass of irrelevant or useless junk and to discover new knowledge via the intelligent analysis of the data. Many of the intelligent tools and techniques discussed here originated well before cloud computing. However, the ...
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    3. Induction of Dependency Structures Based on Weighted Projection

      This paper describes a novel weighted projection method of inducing grammatical dependency structures for Polish. Using a parallel English-Polish corpus, the English side is automatically annotated with a syntactic parser and the resulting annotations are projected to Polish via word alignment links. Projected arcs are weighted according to the certainty of word alignment links used in the projection, where arcs projected via intersection links are weighted with the lowest value (corresponding to the highest certainty). Minimum spanning trees induced from such graphs are used to train a parsing model with a publicly available parser-generation system. Content Type Book ChapterPages 364-374DOI ...
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    4. Mediating Accesses to Multiple Information Sources in a Multi-lingual Application

      This paper describes an approach to mediating accesses to multiple information sources in a multi-lingual application. There are many information sources available on the Internet in different languages, and machine translation services are also available to allow multi-lingual access to information sources. Domain-dependent translation dictionaries are often used to make translation more appropriate. In the proposed approach, the domain-dependent translation dictionaries are represented as linked data. Using the data available from the translation dictionaries, accesses to the information sources that are represented as linked data can be customized. By applying the linked data concept, a multi-lingual application can be constructed ...
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    5. An Approach to Extraction of Linguistic Recommendation Rules – Application of Modal Conditionals Grounding

      An approach to linguistic summarization of distributed databases is considered. It is assumed that summarizations are produced for the case of incomplete access to existing data. To cope with the problem the stored data are processed partially (sampled). In consequence summarizations become equivalent to the natural language modal conditionals with modal operators of knowledge, belief and possibility. To capture this case of knowledge processing an original theory for grounding of modal languages is applied. Simple implementation scenarios and related computational techniques are suggested to illustrate a possible utilization of this model of linguistic summarization. Content Type Book ChapterPages 249-258DOI 10 ...
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    6. A On-Line News Documents Clustering Method

      To improve the efficiency and accuracy of on-line news event detection (ONED) method, we select the words that their term frequency (TF) is greater than a threshold to create the vector space model of the news document, and propose a two-stage clustering method for ONED. This method divides the detection process into two stages. In the first stage, the similar documents collected in a certain period of time are clustered into micro-clusters. In the second stage, the micro-clusters are compared with previous event clusters. The experimental results show that the proposed method has fewer computation load, higher computing rate, and ...
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    7. Detection and Extracting of Emergency Knowledge from Twitter Streams

      Increasingly, more important information is being shared through Twitter. New opportunities arise to use this tool to detect emergencies and extract crucial information about the scope and nature of that event. A major challenge for the extraction of emergency event information from Twitter is represented by the unstructured and noisy nature of tweets. Within the SABESS project we propose a combined structural and content based analysis approach. We use social network analysis to identify reliable tweets and content analysis techniques to summarize key emergency facts. Content Type Book ChapterPages 462-469DOI 10.1007/978-3-642-35377-2_64Authors Bernhard Klein, Deusto Institute of Technology, DeustoTech ...
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      Mentions: Spain Bilbao Asturias
    8. A System for Epileptic Seizure Focus Detection Based on EEG Analysis

      This work presents a recognition system for epileptiform abnormalities based on electroencephalogram (EEG) analysis. The proposed system combines a Support Vector Machine classifier automatically trained by an implementation of machine learning approach known as Bag of Words. Content Type Book ChapterPages 407-414DOI 10.1007/978-3-642-35377-2_57Authors Maria Jose Santofimia Romero, Computer Architecture and Network Group, School of Computing Science, University of Castilla-La Mancha, SpainXavier del Toro, Computer Architecture and Network Group, School of Computing Science, University of Castilla-La Mancha, SpainJesús Barba, Computer Architecture and Network Group, School of Computing Science, University of Castilla-La Mancha, SpainJulio Dondo, Computer Architecture and Network Group ...
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    9. CrowdLang: A Programming Language for the Systematic Exploration of Human Computation Systems

      Human computation systems are often the result of extensive lengthy trial-and-error refinements. What we lack is an approach to systematically engineer solutions based on past successful patterns. In this paper we present the CrowdLang programming framework for engineering complex computation systems incorporating large crowds of networked humans and machines with a library of known interaction patterns. We evaluate CrowdLang by programming a German-to-English translation program incorporating machine translation and a monolingual crowd. The evaluation shows that CrowdLang is able to simply explore a large design space of possible problem-solving programs with the simple variation of the used abstractions. In an ...
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    10. Experiments in Cross-Lingual Sentiment Analysis in Discussion Forums

      One of the objectives of sentiment analysis is to classify the polarity of conveyed opinions from the perspective of textual evidence. Most of the work in the field has been intensively applied to the English language and only few experiments have explored other languages. In this paper, we present a supervised classification of posts in French online forums where sentiment analysis is based on shallow linguistic features such as POS tagging, chunking and common negation forms. Furthermore, we incorporate word semantic orientation extracted from the English lexical resource SentiWordNet as an additional feature. Since SentiWordNet is an English resource, lexical ...
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    11. An efficient heuristic method for active feature acquisition and its application to protein-protein interaction prediction

      Abstract Background  Machine learning approaches for classification learn the pattern of the feature space of different classes, or learn a boundary that separates the feature space into different classes. The features of the data instances are usually available, and it is only the class-labels of the instances that are unavailable. For example, to classify text documents into different topic categories, the words in the documents are features and they are readily available, whereas the topic is what is predicted. However, in some domains obtaining features may be resource-intensive because of which not all features may be available. An example is ...
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    12. Recognition of medication information from discharge summaries using ensembles of classifiers

      Abstract Background  Extraction of clinical information such as medications or problems from clinical text is an important task of clinical natural language processing (NLP). Rule-based methods are often used in clinical NLP systems because they are easy to adapt and customize. Recently, supervised machine learning methods have proven to be effective in clinical NLP as well. However, combining different classifiers to further improve the performance of clinical entity recognition systems has not been investigated extensively. Combining classifiers into an ensemble classifier presents both challenges and opportunities to improve performance in such NLP tasks. Methods  We investigated ensemble classifiers that used ...
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    13. The cross-lingual lexical substitution task

      Abstract  In this paper we provide an account of the cross-lingual lexical substitution task run as part of SemEval-2010. In this task both annotators (native Spanish speakers, proficient in English) and participating systems had to find Spanish translations for target words in the context of an English sentence. Because only translations of a single lexical unit were required, this task does not necessitate a full blown translation system. This we hope encouraged those working specifically on lexical semantics to participate without a requirement for them to use machine translation software, though they were free to use whatever resources they chose ...
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    14. Knowledge acquisition through human–robot multimodal interaction

      Abstract  The limited understanding of the surrounding environment still restricts the capabilities of robotic systems in real world applications. Specifically, the acquisition of knowledge about the environment typically relies only on perception, which requires intensive ad hoc training and is not sufficiently reliable in a general setting. In this paper, we aim at integrating new acquisition devices, such as tangible user interfaces, speech technologies and vision-based systems, with established AI methodologies, to present a novel and effective knowledge acquisition approach. A natural interaction paradigm is presented, where humans move within the environment with the robot and easily acquire information by ...
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    15. Multi-view constrained clustering with an incomplete mapping between views

      Abstract  Multi-view learning algorithms typically assume a complete bipartite mapping between the different views in order to exchange information during the learning process. However, many applications provide only a partial mapping between the views, creating a challenge for current methods. To address this problem, we propose a multi-view algorithm based on constrained clustering that can operate with an incomplete mapping. Given a set of pairwise constraints in each view, our approach propagates these constraints using a local similarity measure to those instances that can be mapped to the other views, allowing the propagated constraints to be transferred across views via ...
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    16. Portuguese text generation using factored language models

      Abstract  As in many other natural language processing (NLP) fields, the use of statistical methods is now part of mainstream natural language generation (NLG). In the development of systems of this kind, however, there is the issue of data sparseness, a problem that is particularly evident in the case of morphologically-rich languages such as Portuguese. This work presents a shallow surface realisation system that makes use of factored language models (FLMs) of Portuguese to overcome some of these difficulties. The system combines FLMs trained on a large corpus with a number of NLP resources that have been made publicly available ...
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    17. Parallels between Machine and Brain Decoding

      We report some existing work, inspired by analogies between human thought and machine computation, showing that the informational state of a digital computer can be decoded in a similar way to brain decoding. We then discuss some proposed work that would leverage this analogy to shed light on the amount of information that may be missed by the technical limitations of current neuroimaging technologies. Content Type Book ChapterPages 162-174DOI 10.1007/978-3-642-35139-6_16Authors Lorenzo Dell’Arciprete, Artificial Intelligence Research, University of Rome Tor Vergata, Rome, ItalyBrian Murphy, Machine Learning Department, Carnegie Mellon University, Pittsburgh, USAFabio Massimo Zanzotto, Artificial Intelligence Research, University ...
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    18. Rule-Based Morphological Tagger for an Inflectional Language

      This paper aims to present an alternative view on the task of morphological tagging - a rule based system with new and simple learning method that uses just basic arithmetic operations to create an efficient knowledge base. Matching process of this rule-based approach follows specific-to-general technique, where rules for more specific contexts are applied whenever they are available in the rule-base. As a consequence, the major accuracy and performance improvements can be achieved by pruning the rule-base. Content Type Book ChapterPages 208-215DOI 10.1007/978-3-642-34584-5_17Authors Daniel Hládek, Department of Electronics and Multimedia Communications, Faculty of Electrical Engineering and Informatics, Technical University ...
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    19. An Approach to Intelligent Signal Processing

      This paper describes an approach to intelligent signal processing. First we propose a general signal model which applies to speech, music, biological, and technical signals. We formulate this model mathematically using a unification of hidden Markov models and finite state machines. Then we name tasks for intelligent signal processing systems and derive a hierarchical architecture which is capable of solving them. We show the close relationship of our approach to cognitive dynamic systems. Finally we give a number of application examples. Content Type Book ChapterPages 1-18DOI 10.1007/978-3-642-34584-5_1Authors Matthias Wolff, Lehrstuhl Kommunikationstechnik, Brandenburgische Technische Universität Cottbus, 03046 Cottbus, GermanyRüdiger ...
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    20. Positive Effects in Detecting Lies from Training to Recognize Behavioral Anomalies

      Abstract  We examined whether training in both the verbal and nonverbal indicators of truth telling and lying would have positive effects on Law Enforcement Officers’ (LEOs) ability to evaluate truths from lies. College course-level training on empirically validated verbal and nonverbal indicators of truth telling and lying was provided to mid- to advanced-career level LEOs, whose accuracy in detecting lies from truths was assessed pre- and post-training using truthful and deceptive videos of mock crimes and opinions. A marginally significant truth bias existed at pre-test; training, however, resulted in a significant improvement in accuracy rates for both truth and lie ...
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    21. Supervised segmentation of phenotype descriptions for the human skeletal phenome using hybrid methods

      Abstract Background  Over the course of the last few years there has been a significant amount of research performed on ontology-based formalization of phenotype descriptions. In order to fully capture the intrinsic value and knowledge expressed within them, we need to take advantage of their inner structure, which implicitly combines qualities and anatomical entities. The first step in this process is the segmentation of the phenotype descriptions into their atomic elements. Results  We present a two-phase hybrid segmentation method that combines a series individual classifiers using different aggregation schemes (set operations and simple majority voting). The approach is tested on ...
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    22. A text-mining system for extracting metabolic reactions from full-text articles

      Abstract Background  Increasingly biological text mining research is focusing on the extraction of complex relationships relevant to the construction and curation of biological networks and pathways. However, one important category of pathway — metabolic pathways — has been largely neglected. Here we present a relatively simple method for extracting metabolic reaction information from free text that scores different permutations of assigned entities (enzymes and metabolites) within a given sentence based on the presence and location of stemmed keywords. This method extends an approach that has proved effective in the context of the extraction of protein–protein interactions. Results  When evaluated on a ...
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    23. Modeling the impact of review dynamics on utility value of a product

      Abstract  Manufacturer-provided specifications often do not provide a true picture of the utility value of a product. A product’s true assessed value is the result of consumer opinion often conveyed via word of mouth. The increasing popularity of social media has led to the inevitable integration of the social platform with e-commerce sites where consumers share their opinions on products and prospective buyers seek the opinion of their peers before making a purchase. The influencing power of these social platforms has led to researchers mining these opinions and utilizing them to assess the value of the product. Consumer opinion ...
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    24. Research, Innovation, Entrepreneurship and the Rentier Culture in the Arab Countries

      While the average age varies from one country to another, collectively the Arabs constitute one of the world’s most youthful populations. For Arab governments with few or no social services, dysfunctional educational systems and inadequate innovation and entrepreneurial capabilities, their young populations are rapidly turning from an onerous burden into a grave menace. This chapter reviews a number of critical challenges that need to be addressed to rectify the situation, with special emphasis on the GCC countries and with reference to the rentier culture that pervades many walks of life across the region. Compounded by persistent ethnic, religious and ...
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      Mentions: Lebanon Beirut GCC
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      Discourse, Entailment, Machine Translation, NER, Parsing, Segmentation, Semantic, Sentiment, Summarization, WSD