Top PDF Ontology-based Semi-automatic Workflow Composition

Ontology-based Semi-automatic Workflow Composition

Ontology-based Semi-automatic Workflow Composition

We analyzed existing SWfMS support for workflow representation in different levels of abstractions and the semantic support for the process of composing scientific workflows. Available SWfMS are restricted to concrete level. In this way, the knowledge of which activities can be linked to each other is still tacit. Currently, projects in many domains force scientists to redefine, almost from scratch, scientific workflows previously developed by other scientists, incurring in the same composition trial and error process. This occurs due to the absence of a systematic approach for composition and lack of abstract workflow representation. Some approaches use ontologies to help composing scientific workflows. One example is the TAMBIS [Stevens et al. 2000] project that aims to provide transparent access to biological databases and scientific analysis tools. It provides a knowledge driven interface where the scientist is able to compose experiments in terms of biological terminology. It focuses on a specific domain (biology) and does not represent generic workflow metadata. In the same direction, the approach proposed by [Wolstencroft et al. 2007] proposes an ontology based on a specific project. [Altintas and Ludascher 2003] present an approach to relieve the scientists from designing directly executable workflows. It represents an abstract workflow based on directed acyclic graphs. It uses database mediation techniques that automatically map abstract workflow activities into executable ones. This mapping is powerful and independent of SWfMS. However, this approach does not add semantics to the abstract activity, thus identifying similar workflows that share a common ancestor is not possible. OWL-WS [Beco et al. 2005] is a semantic workflow representation model with a related language that is workflow ontology. The objective is to define a workflow language that enables a specification of dynamic workflows, which are composed of Grid Services and are used as evaluation and binding mechanisms in a Grid Service enactment engine. Although OWL-WS offers a meta- model for scientific workflows, it focuses on concrete workflow representation to model services, ports and infrastructure issues, lacking support for modeling a conceptual representation of a workflow in different levels of abstraction.
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A Workflow Based Failure Recovery in Web Services Composition

A Workflow Based Failure Recovery in Web Services Composition

The first factor is the language or technology depen- dency. All four methods including ours are language in- dependent. The second factor is the support for an auto- mated method to generate the fault-tolerance mechanisms from the high level specifications. Our proposed method supports automatic generation of reliable workflow from rollback dependencies. The third factor is the recovery support, which means if a service fails how the composi- tion continues in order to terminate in a consistent state. The first method uses redundant services without any recovery support. The second method tries to terminate the composition in a consistent state. In contrast, in our work a rollback method for failed services with mini- mum cost is supported. The forth factor is the fault tol- erance technique applied by each method. The fifth fac- tor is the existence of a theoretical foundation to sup- port the fault tolerance or recovery. The first method uses the FSP language to be able to evaluate the correctness of its model. We also have used the FSP language as a for- mal language as a workflow specification language for assessing the correctness of the resulted workflow. The FSP language chosen in this paper, allowed us to present
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Design of a Novel Semi Automatic Coconut Tree Climbing Device

Design of a Novel Semi Automatic Coconut Tree Climbing Device

The aim of this study is to present a novel semi-automatic coconut tree climbing device and validate its strength based on actual working conditions. Firstly, the structural composition and operational principal of this device is introduced. After that, the finite element model of this device is established with CATIA. Finally, the strength analysis is executed by means of CATIA. In this study, the equivalent stress, principal stress, and displacement contours are obtained. The simulation results show that the maximum stress of this device is below 355 MPa, which is the value of the yield strength. Therefore, this device is capable of satisfying practical application requirements.
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Semi-Automatic Domain Ontology Creation from Text Resources

Semi-Automatic Domain Ontology Creation from Text Resources

Analysts in various domains, especially intelligence and financial, have to constantly extract useful knowledge from large amounts of unstructured or semi-structured data. Keyword-based search, faceted search, question-answering, etc. are some of the automated methodologies that have been used to help analysts in their tasks. General-purpose and domain-specific ontologies have been proposed to help these automated methods in organizing data and providing access to useful information. However, problems in ontology creation and maintenance have resulted in expensive procedures for expanding/maintaining the ontology library available to support the growing and evolving needs of analysts. In this paper, we present a generalized and improved procedure to automatically extract deep semantic information from text resources and rapidly create semantically-rich domain ontologies while keeping the manual intervention to a minimum. We also present evaluation results for the intelligence and financial ontology libraries, semi-automatically created by our proposed methodologies using freely-available textual resources from the Web.
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OCR4all - An Open-Source Tool Providing a (Semi-)Automatic OCR Workflow for Historical Printings

OCR4all - An Open-Source Tool Providing a (Semi-)Automatic OCR Workflow for Historical Printings

To deal with these issues, we present our open-source tool OCR4all 34 which aims to encapsulate a comprehensive OCR workflow into a single Docker 5 application, ensuring easy installation and platform independency. The goal is to make the capabilities of state of the art tools like OCRopus or Calamari available within a comprehensible and applicable semi-automatic workflow to basically any given user. This is achieved by supplying the users with a comfortable and easy to use GUI and a modular approach, allowing for an efficient correction process in between the various workflow steps in order to minimize the negative effects of consequential errors. Another important aspect is the option to iteratively reduce the CER by constantly retraining the recognition models on additional training data which has been created during the processing of a given book. During development the primary goal was to identify a workflow and tool composition which enables the users to deal with even the earliest printed books on their own and extract their textual content with great quality. Due to the challenges concerning condition, layout and typography described above, this is far from a trivial task and often requires the users to invest a substantial amount of manual effort into correcting segmentation results and transcribing line images in order to produce training data for the book specific models. However, in our experience, humanist scholars who are dealing with early printed books are usually perfectly fine with investing the required effort to obtain high quality OCR results which had been considered almost impossible to achieve on this material only a decade ago [14]. This is especially true since the alternatives are either to manually transcribe everything or to not get to the text at all. Naturally, we did not want to restrict the users to the processing of very early printed
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Volume 44: OCL and Textual Modelling 2011

Volume 44: OCL and Textual Modelling 2011

ASSL has been implemented in combination with the parser generator ANTLR [11]. However, this article does not focus on implementation details. It rather explains how we use the extensions in the context of UML metamodel-based workflow execution. We are confident that there is a number of further promising applications of the proposed ASSL extensions. Especially the area of model testing and certification in connection with the unique commands Try and Any for semi-automatic snapshot generation seems to bear good prospects for use. The workflow modeling and execution approach is a new application for the USE tool and ASSL. The presented approach comprises of a declarative and an imperative part, while the focus of this article is on the imperative part. Our approach enables us to express the workflow patterns presented in [12]. In contrast to established workflow languages like EPCs, UML activity diagrams or BPMN the modeling approach has a flexible background driven by design principles. All execution sequences of the process model are allowed if they are not forbidden by OCL constraints. In contrast, the established languages uses a more Petri net-like modeling approach in which only the allowed execution flows are determined. The developer defines action sequences that may restrict the user too much while executing the workflow [13]. In our view, the work presented in this paper is a new direction in the context of workflow languages with a declarative metamodel-based approach.
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Responsible team players wanted: an analysis of soft skill requirements in job advertisements

Responsible team players wanted: an analysis of soft skill requirements in job advertisements

During the past decades the importance of soft skills for labour market outcomes has grown substantially. This carries implications for labour market inequality, since previous research shows that soft skills are not valued equally across race and gender. This work explores the role of soft skills in job advertisements by drawing on methods from computational science as well as on theoretical and empirical insights from economics, sociology and psychology. We present a semi-automatic approach based on crowdsourcing and text mining for extracting a list of soft skills. We find that soft skills are a crucial component of job ads, especially of low-paid jobs and jobs in female-dominated professions. Our work shows that soft skills can serve as partial predictors of the gender composition in job categories and that not all soft skills receive equal wage returns at the labour market. Especially “female” skills are frequently associated with wage penalties. Our results expand the growing literature on the association of soft skills on wage inequality and highlight their importance for occupational gender segregation at labour markets.
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Web based Knowledge Extraction and Consolidation for Automatic Ontology Instantiation

Web based Knowledge Extraction and Consolidation for Automatic Ontology Instantiation

Using ontologies to back up IE is hoped to support informa- tion integration [2][18] and increase domain portability [10][11]. Poibeau [16] investigated increasing domain in- dependency by using clustering methods on text corpuses to aid users construct primitive ontologies to represent the main corpus topics. Templates could then be generated from the ontology and guide the IE process. Ontologies produced by this approach are limited to the content of the corpus, rather than representing a specific domain. In some cases (such as in Artequakt) the corpus is very large and diverse (e.g. the Web). Creating ontologies from such cor- pus is infeasible. Furthermore, these ontologies are likely to be rough, shallow, and include undesired concepts that hap- pen to be in the text corpus. Consequently, the cost of bringing such ontologies to shape might exceed the benefit. Instantiating ontologies with assertions from textual docu- ments can be a very laborious task. A number of tools have been developed that instantiate ontologies semi automati- cally with user driven annotations [20]. IE learning tools, such as Amilcare [4], can be used to automate part of the annotation process and speed up ontology instantiation [7][21].
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Architecture based Comparison of Semantic Web Service Composition Processes

Architecture based Comparison of Semantic Web Service Composition Processes

A workflow is abstraction of a business process. It comprises of tasks, dependencies among tasks, rules and participants. Task represent a software system in which task flow from one web services to another service and performed appropriate functionality. OWL-S process model [2] is work flow driven model for web service composition. This model uses DAML based match maker. Workflow is composed with help of composite and atomic processes. Various compositions constructs like conditional and looping constructs are used to perform automated composition. Knowledge based approaches used domain knowledge for composition and selection of services and also used WSDL [9] to accompanied the description and execute the workflow. Framework must comprise of knowledge representations and ontology, web services modules, semantic environment. Input request matching also uses work flow pattern, this matching process is used to find services available for clients input request and output matching is done with last service in work flow.
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Automatic Ontology Based Knowledge Extraction from Web Documents

Automatic Ontology Based Knowledge Extraction from Web Documents

Populating ontologies with a high quantity and quality of instantiations is one of the main steps towards providing valuable and consistent ontology-based knowledge services. Manual ontology population is very labour intensive and time consuming. Some semi-automatic approaches have investigated creating document annotations and storing the results as assertions in an ontology. For example in Vargas Vera et al (2001), relationships were added automatically between instances only if these instances already exist in the KB, otherwise user intervention is needed. Handschuh et al (2002) describe a framework for user-driven ontology-based annotations, enforced with the IE learning tool; Amilcare (Ciravegna et al 2002). However, the framework lacks the capability of identifying relationships reliably.
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Automatic Extraction of Concepts of the Request Submitted to the IRS Based on Ontology

Automatic Extraction of Concepts of the Request Submitted to the IRS Based on Ontology

In this section we present the main methods used to extract the semantic fields from a corpus which will also be used to extract concepts from the user query. The latter is made by an expert of domain and turns out very expensive. To extract the descriptors of a field automatically or semi- automatically, a corpus of expertise must be used, then the techniques of automatic language processing is applied to the corpus. Finally, to extract all descriptors of a field in an automatic way, it is essential to use a corpus that covers the entire area. In the literature, the various works of extraction of the concepts from the textual corpuses use two approaches, namely the statistical analysis and the linguistic analysis (CLAVEAU [14]). The statistical analysis bases itself on the study of the contexts of use and the distributions of the terms in documents. The linguistic analysis exploits linguistic knowledge, such as the morphological or syntactical structures of the terms. Other works couple these two approaches and constitute an approach called "hybrid or mixed approach".
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Semi Automatic to Improve Ontology Mapping Process in Semantic Web Data Analysis

Semi Automatic to Improve Ontology Mapping Process in Semantic Web Data Analysis

A GUI based system AI-ATOM is developed as a prototype for the proposed integrated approach. The system consists of five horizontal components, viz., Ontology Management, Ontology Project Management, User Management, System Configuration and Ontology Mapping Engine; and six vertical components, viz., Language Processing, VSM Engine, Label Matcher, Linguistic Matcher, Structure Matcher, and User Interaction[5]. The brief description of each component is given below. It allows the user to create new ontology, maintain an existing ontology, delete existing ontology, and to import ontology from file containing parenthesized tree. While user creates new ontology, the system suggests the concept labels along with their meaning from the user specified context dictionary (Domain Specific Labels), based on its usage frequency, that are best matching with partially entered labels by user. The context dictionary is maintained with the help oftable. This helps the user from typing and thinking different label from intention of the community of users in the same domain. This helps a lot when two suchontologies need to be mapped later. Thus, systemproposed here tries to improve ontology mapping process right from its creation.
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Semi-Automatic Ontology Extension Using Spreading Activation

Semi-Automatic Ontology Extension Using Spreading Activation

Heuristic rules common in text mining and natural language processing face a number of shortcomings in automatically discovering semantic relationships between domain concepts. Attempts to semi-automatically extend and refine domain-specific ontologies call for a more fine-grained processing of textual data. Based on a corpus gathered from a large sample of news media sites, a novel approach to finding semantic concept relations using spreading activation on weighted graphs has been proposed and combined with existing heuristics.

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Discovery and evaluation of non-taxonomic relations in domain ontologies

Discovery and evaluation of non-taxonomic relations in domain ontologies

The research presented in this paper focuses on adding link type discovery to a semi-automatic ontology extension architecture that builds domain specific ontologies based on a small seed on- tology and a domain-specific corpus containing a large number of unstructured Web documents. Our approach distinguishes between taxonomic and non-taxonomic relations. It detects tax- onomic relations by facilitating customized natural language processing techniques and databases. The non-taxonomic cat- egory is based on previously learned relations, assuming that similar relations between concepts are expressed via similar verbs. Comparing the vector space representation of verbs co- occurring with the target concepts to known verb-vectors using the cosine similarity metric yields the relation type of the un- known relation. Suggestions and evaluations from domain ex- perts are fed back into the architecture adjusting its KB, leading to a constant improvement of the algorithm’s accuracy.
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A Meta data Driven Platform for Semi automatic Configuration of Ontology Mediators

A Meta data Driven Platform for Semi automatic Configuration of Ontology Mediators

From this viewpoint, we must solve a coordination task, i.e. finding the mediator that will achieve the user goals against the given ontologies, and properly configuring it to deal with the specific mediation scenario. The MAPLE coordinator performs this task, by exploiting metadata about the input ontologies, the mediators, the linguistic resources and other components. While the set of relevant features is probably endless, we focus mostly on linguistic aspects. In fact, our proposal builds on, extends and updates our previous work on linguistic coordination of communicating agents (Pazienza, et al., 2007). While the underlying principles remain the same, the current work differs substantially for its grounding in the Linked Data world and the shift to component-based architectures.
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Ontology based semantic annotation: an automatic hybrid rule based method

Ontology based semantic annotation: an automatic hybrid rule based method

In a rule-based information extraction or seman- tic annotation system, annotation rules are usually written by a domain expert. However, these rules can be learned using a rule-based learning algo- rithm. The TextRuler system (Kluegl et al., 2009) is a framework for semi-automatic development of rule-based information extraction applications that contains some implementations of such algo- rithms ((LP) 2 (Ciravegna, 2001; Ciravegna, 2003), WHISK (Soderland et al., 1999), RAPIER (Califf and Mooney, 2003), BWI (Freitag and Kushmer- ick, 2000) and WIEN (Kushmerick et al., 1997)). TextRuler is based on Apache UIMA TextMarker which is a rule-based script language.
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Towards Semi Automatic Construction of a Lexical Ontology for Persian

Towards Semi Automatic Construction of a Lexical Ontology for Persian

In recent years, there has been an increasing interest in semantic processing of natural languages. Some of the essential resources to make this kind of process possible are semantic lexicons and ontologies. Lexicon contains knowledge about words and phrases as the building blocks of language and ontology contains knowledge about concepts as the building blocks of human conceptualization (the world model) (Shamsfard & Barforoush, 2003). Lexical ontologies or NL-ontologies are ontologies whose nodes are lexical units of a language. Moving from lexicons toward ontologies by representing the meaning of words by their relations to other words, results in semantic lexicons and lexical ontologies. One of the most popular semantic lexicons for English is WordNet. Princeton WordNet (Fellbaum, 1998), is widely used in NLP research works. It covers English language and has been first developed by Miller in a hand-crafted way. Many other lexical ontologies (such as EuroWordNet, BalkaNet, …) have been created based on Princeton wordnet for other languages such as Dutch, Italian, Spanish, German, French, Czech and Estonian. Although there are such semantic, lexical resources for English and some other languages, some languages such as Persian (Farsi) lack such a semantic resource for use in NLP works.
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An ontology-based approach to Automatic Generation of GUI for Data Entry

An ontology-based approach to Automatic Generation of GUI for Data Entry

This thesis reports an ontology-based approach to automatic generation of highly tailored GUI components that can make customized data requests for the end users. Using this GUI generator, without knowing any programming skill a domain expert can browse the data schema through the ontology file of his/her own field, choose attribute fields according to business’s needs, and make a highly customized GUI for end users’ data requests input. The interface for the domain expert is a tree view structure that shows not only the domain taxonomy categories but also the relationships between classes. By clicking the checkbox associated with each class, the expert indicates his/her choice of the needed information. These choices are stored in a metadata document in XML. From the viewpoint of programmers, the metadata contains no ambiguity; every class in an ontology is unique. The utilizations of the metadata can be various; I have carried out the process of GUI generation. Since every class and every attribute in the class has been formally specified in the ontology, generating GUI is automatic. This approach has been applied to a use case scenario in meteorological and oceanographic (METOC) area. The resulting features of this prototype have been reported in this thesis.
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Ontorat: automatic generation of new ontology terms, annotations, and axioms based on ontology design patterns

Ontorat: automatic generation of new ontology terms, annotations, and axioms based on ontology design patterns

We have developed the web-based Ontorat tool that implements the ontology enrichment strategy shown in Figure 1. Figure 2 lays out the Ontorat design and work- flow pipeline. Specifically, on the Ontorat web page, a user enters setting options and uploads the input data file via the Ontorat web input form. The input data file is gener- ated by populating a predesigned template file guided by the ODP as mentioned above. After accepting the input data file and setting options from the user, the web server (via a PHP script) will be able to execute two operations: 1) generation of new ontology classes with logical axioms and annotations, or 2) addition of new axioms to existing ontology terms. The Ontorat server will process the user’s requests and generate either an Ontorat settings file or an OWL output file. The Ontorat settings file can be stored and reused later. For the OWL output generation, a Manchester syntax file will be generated first and then transferred to OWL format (Figure 2).
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iPOJO flow:a declarative service workflow architecture for ubiquitous cloud applications

iPOJO flow:a declarative service workflow architecture for ubiquitous cloud applications

Lastly, besides its basic abstraction of services, the OSGi specification has introduced declarative service supports such as Blueprint Container Service and Declarative Service(The OSGi Alliance 2014). iPOJO component model is another such effort. They all intend to ease the complexity of building a composite application and managing its dependencies based on a composition description. A number of advanced platforms have emerged with the advent of iPOJO to facilitate the development of dynamic pervasive applications based on OSGi frameworks in distributed environments. For instance, the SmartComponent Framework is introduced to build sensor clouds with the purpose to manipulate, access, and visualize information distrusted sensors (Neto et al. 2015). Also, two iPOJO-based middleware, named Cilia and iCasa, is proposed to help construct pervasive health and smart manufacturing applications which require a high degree of flexibility at runtime (Lalanda et al. 2017; Lalanda et al. 2015). However, their emphasis is not on service composition support to enable iPOJO component-based pervasive applications. Specifically, Cilia essentially focuses on device integrations but not services. iCasa is mostly concerned about context-aware service composition instead of workflow-based orchestrations. In general, these existing works lack proper support for declarative service composition of diversified topologies, which had led us to develop iPOJO Flow service composition framework.
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