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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. Languages for Constructing DEVS Models

      Languages for Constructing DEVS Models
      This chapter first provides a higher level perspective on the approach that MS4 Me™ takes to computational support for constructing DEVS models for virtual build and test. After describing this approach, we expand our view to examine whether Unified Modeling Language (UML) can provide a more expressive framework for DEVS specification. For completeness we also look at how UML can serve as a target for implementation of DEVS models. Content Type Book ChapterPages 165-176DOI 10.1007/978-0-85729-865-2_12Authors Bernard P. Zeigler, Chief Scientist, RTSync Corp., Rockville, MD, USAHessam S. Sarjoughian, Computer Science & Engineering Faculty, Arizona State University, Tempe, AZ, USA Book ...
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    3. Enterprise Search and Retrieval (ESR): The Binding Factor

      Enterprise Search and Retrieval (ESR): The Binding Factor
      This chapter on enterprise search and retrieval (ESR) discusses the capabilities of search engines to process content but also people’s ability to find what they are looking for. Both the state of technology as well as psychological aspects play a role in this. Content Type Book ChapterPages 175-209DOI 10.1007/978-1-4614-5236-2_7Authors Anja van der Lans, Advisory Services, Incentro, De Meern, The Netherlands Book Series Management for ProfessionalsOnline ISSN 2192-810XPrint ISSN 2192-8096 Book Series Volume Volume 2 Book Enterprise Information ManagementDOI 10.1007/978-1-4614-5236-2Online ISBN 978-1-4614-5236-2Print ISBN 978-1-4614-5235-5
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    4. Intelligence in the Cloud

      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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    5. Multimodal Queries to Access Multimedia Information Sources: First Steps

      This position paper deals with queries beyond text, mixing several multimedia contents: audio, video, image and text. Search approaches combining some of these formats have been studied, including query by example techniques in situations where only one format is considered. It is worth mentioning that most of these research works do not deal with text content. A new approach to allow users introducing multimodal queries and exploring multimedia repositories is proposed. For this purpose, different ranked result lists must be combined to produce the final results shown for a given query. The main goal of this proposal is to reduce ...
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    6. Active Learning with Bagging for NLP Tasks

      Supervised classifiers are limited by the annotated corpora available. Active learning is a way to circumvent this bottleneck, reducing the number of annotated examples required. In this paper, we analyze the benefits of active learning combined with bagging applied to Quotation Start, Noun Phrase Chunking and Text Chunking tasks. We employ query-by-committee as query strategy to actively select examples to be annotated. By using these techniques, we achieve reductions up to 62.50% on the annotation effort depending on the task to obtain the same quality as in passive supervised learning. Content Type Book ChapterPages 141-147DOI 10.1007/978-3-642-30111-7_14Authors Ruy ...
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    7. Chinese Semantic Role Labeling Based on the Hybrid Convolution Tree Kernel

      Rencently there have been a revived interst in semantic parsing by pplying statistical and machine learning methods to semantically annotated corpora such as the FrameNet and the Proposition Bank. So far much of the research has been focused on English due to the lack of semantically annotated resources in other languages, such as Chinese. In this paper, we use the convolution tree kernel to decompose these larger structure features and compute the kernel function in polynomial time. This paper provides hybrid convolution tree kernel to make fusion different convolution tree kernels, which can model different features with different kernels. The ...
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    8. Behavioral Profile Generation for 9/11 Terrorist Network Using Efficient Selection Strategies

      In recent days terrorism poses a threat to homeland security. It’s highly motivated by the “net-war” where the extremist are organized in a network structure. The major problem faced is to automatically identify the key player who can maximally influence other nodes in a large relational covert network. The nodes and links are represented in the form of a directional semantic graph where each node is related with more than one relationship with the other node. The behaviors of nodes are analyzed based on the semantic profile generated. This analysis helps the crime analyst to judge the key player ...
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    9. Inferring Gene Interaction Networks

      Inferring Gene Interaction Networks
      This chapter contains the original research results on the monograph. We study the problem of reverse-engineering context-specific, genome-wide interaction networks from expression data. Two existing classes of methods, namely those based on mutual information and those based on Bayesian networks, are described first. Then a new algorithm, based on the so-called phi-mixing coefficient between random variables, is introduced. Unlike mutual information, the phi-mixing coefficient provides a directionally sensitive measure of the dependence between two random variables. The algorithm based on this new approach produces a gene interaction network in the form of a directed, strongly connected graph. The approach is ...
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    10. 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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    11. 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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    12. Robust Plagiary Detection Using Semantic Compression Augmented SHAPD

      This work presents results of the ongoing novel research in the area of semantic networks, plagiarism detection and general natural language processing. Results presented here demonstrate that the semantic compression is a valuable addition to the existing methods used in plagiary detection. The application of the semantic compression boosts the efficiency of Sentence Hashing Algorithm for Plagiarism Detection (SHAPD) and authors’ implementation of the w-shingling algorithm. There were also test with use of the traditional Vector Space Model method that demonstrated that this technique is not well suited for plagiary detection contrary to general beliefs. All the experiments were performed ...
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    13. Ripple Down Rules for Vietnamese Named Entity Recognition

      One of the biggest problems with rule based systems is how to avoid the conflict between rules when a new rule is added. Ripple Down Rules (RDR) is considered a good systematic approach to address this for classification problems. In this paper, we present a system using RDR to build the set of rules for Vietnamese Named Entity Recognition which is important for many natural language processing tasks. Experimental results on comparing the proposed approach with a standard method where rules are added in an ad-hoc manner prove to be very promising. Content Type Book ChapterPages 354-363DOI 10.1007/978-3-642-34630-9_37Authors ...
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    14. 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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    15. A Hybrid Approach of Pattern Extraction and Semi-supervised Learning for Vietnamese Named Entity Recognition

      Requiring a large hand-annotated corpus in supervised learning of contemporary Vietnamese Named Entity Recognition researches is challenging. We therefore propose a hybrid approach of pattern extraction and semi-supervised learning. Applied rule-based method helps generating patterns automatically. Part-of-speech tagger, lexical diversity and chunking are explored to define rules in pattern extractions which are used for identifying potential named entities. Semi-supervised learning trains a small amount of seed named entities to categorize named entities in extracted patterns. In experiments, our approach shows good increasing the system accuracy with others in Vietnamese. Content Type Book ChapterPages 83-93DOI 10.1007/978-3-642-34630-9_9Authors Duc-Thuan Vo, Natural ...
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    16. Information Extraction from Geographical Overview Maps

      The paper presents a method of information extraction from overview maps. The idea is based on recognizing text located on the map and on finding locations corresponding to the extracted text labels using the GeoNames ontology. The method consists of three phases. The first one performs map image processing in order to recognize text labels. The next phase verifies these labels and marks them as being sure or unsure locations. In the third phase the map is interpreted based on the locations found. The second and third phases make use of the ontology. The preliminary results are promising for further ...
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    17. Generic Operations in the Structured Space of the Music

      In this paper we study the problem of performing operations in structured spaces of data. This problem is one of the few most important aspects of intelligent knowledge processing. For complex spaces of data performing operations requires deep analysis, which usually employs description of the operation, its syntactic structuring and semantic analysis. In the study we focus our attention on employing operation in processing music data. The case study carries out transposition accomplished in printed music notation and in Braille music notation. It is shown that semantic analysis is necessary to transpose in Braille music notation and makes transposition clearer ...
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    18. Sentiment Classification: A Combination of PMI, SentiWordNet and Fuzzy Function

      Discerning a consensus opinion about a product or service is difficult due to the many opinions on the web. To overcome this problem, sentiment classification has been applied as an important approach for evaluation in sentiment mining. Recently, researchers have proposed various approaches for evaluation in sentiment mining by applying several techniques such as unsupervised and machine learning methods. This paper proposes an unsupervised method for classifying the polarity of reviews using a combination of methods including PMI, SentiWordNet and adjusting the phrase score in the case of modification. The experiment results show that the proposed system achieves accuracy ranging ...
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    19. Refining the Judgment Threshold to Improve Recognizing Textual Entailment Using Similarity

      In recent years, Recognizing Textual Entailment (RTE) catches strongly the attention of the Natural Language Processing (NLP) community. Using Similarity is an useful method for RTE, in which the Judgment Threshold plays an important role as the learning model. This paper proposes an RTE model based on using similarity. We describe clearly the solutions to determine and to refine the Judgment Threshold for Improvement RTE. The measure of the synonym similarity also is considered. Experiments on a Vietnamese version of the RTE3 corpus are showed. Content Type Book ChapterPages 335-344DOI 10.1007/978-3-642-34707-8_34Authors Quang-Thuy Ha, College of Technology (UET), Vietnam ...
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    20. Emerging Technology Exploration Using Rare Information Retrieval and Link Analysis

      Emerging Technology Exploration Using Rare Information Retrieval and Link Analysis
      To explore the clues of an emerging technology is essential for a company or an industry so that the company can consider the feasibility of resource allocation to the technology and the industry can observe the developing directions of the technology. Patent data contains plentiful technological information from which it is worthwhile to extract further knowledge. Therefore, a research framework for emerging technology exploration has been formed where rare information retrieval is designed to sift out the rare patents, cluster analysis is employed to generate the clusters, and link analysis is adopted to measure the link strength between the rare ...
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    21. Reasoning about Knowledge from the Web

      In the presence of a vast amount of user generated content evolving around entities such as people, locations, products, events, etc., it seems that documentoriented retrieval is rather old-fashioned. Imagine an HIV-relevant search task that with the goal of finding drugs that may interfere with HIV protease inhibitors. Retrieving an exhaustive list of explicit results (i.e., drugs that may interfere with HIV protease inhibitors) can be crucial for people suffering from HIV, whose health depends on the unmediated effect of protease inhibitors. Moreover it might be desirable to have the drugs in the result list ranked by their probability ...
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    22. EnglishMash: Usability Design for a Natural Mashup Composition Environment

      The design of mashup tools combines elements from end-user development and software composition in the context of the Web. The challenge for mashup tool designers is to provide end-users with suitable abstractions, programming models and tool support for easily composing mashups out of existing Web services and Web data sources. In this paper we describe the design of a natural mashup composition environment based on the EnglishMash controlled natural language. The environment proactively supports users as they are learning the syntax of the EnglishMash language with features such as auto-completion, immediate feedback, live preview of the mashup execution and component ...
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    23. An Innovative Way for Mining Clinical and Administrative Healthcare Data

      A novel method of “predicting” sitter case attribute value is presented in this paper. The method allows users to choose two attributes, seed and target attribute, and to predict the target attribute value of the forthcoming sitter case. The method first retrieves string sequences of the seed attribute according to filters the users set. Then, it finds the words in the sequences and calculates the term frequencies of the words. With the term frequencies, the proposed method uses vector space model to measure the similarity between the testing sequences and the benchmark sequence. At the end, the testing sequence which ...
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    24. 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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    1-24 of 58 1 2 3 »
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      Discourse, Entailment, Machine Translation, NER, Parsing, Segmentation, Semantic, Sentiment, Summarization, WSD