Showing papers on "Ontology (information science) published in 2006"

Learning systems of concepts with an infinite relational model

Abstract: Relationships between concepts account for a large proportion of semantic knowledge. We present a nonparametric Bayesian model that discovers systems of related concepts. Given data involving several sets of entities, our model discovers the kinds of entities in each set and the relations between kinds that are possible or likely. We apply our approach to four problems: clustering objects and features, learning ontologies, discovering kinship systems, and discovering structure in political data.

Large-scale concept ontology for multimedia

Abstract: As increasingly powerful techniques emerge for machine tagging multimedia content, it becomes ever more important to standardize the underlying vocabularies. Doing so provides interoperability and lets the multimedia community focus ongoing research on a well-defined set of semantics. This paper describes a collaborative effort of multimedia researchers, library scientists, and end users to develop a large standardized taxonomy for describing broadcast news video. The large-scale concept ontology for multimedia (LSCOM) is the first of its kind designed to simultaneously optimize utility to facilitate end-user access, cover a large semantic space, make automated extraction feasible, and increase observability in diverse broadcast news video data sets

A survey on ontology mapping

Abstract: Ontology is increasingly seen as a key factor for enabling interoperability across heterogeneous systems and semantic web applications. Ontology mapping is required for combining distributed and heterogeneous ontologies. Developing such ontology mapping has been a core issue of recent ontology research. This paper presents ontology mapping categories, describes the characteristics of each category, compares these characteristics, and surveys tools, systems, and related work based on each category of ontology mapping. We believe this paper provides readers with a comprehensive understanding of ontology mapping and points to various research topics about the specific roles of ontology mapping.

Ontology Learning and Population from Text: Algorithms, Evaluation and Applications

Abstract: In the last decade, ontologies have received much attention within computer science and related disciplines, most often as the semantic web. Ontology Learning and Population from Text: Algorithms, Evaluation and Applications discusses ontologies for the semantic web, as well as knowledge management, information retrieval, text clustering and classification, as well as natural language processing. Ontology Learning and Population from Text: Algorithms, Evaluation and Applications is structured for research scientists and practitioners in industry. This book is also suitable for graduate-level students in computer science.

Emotion Recognition System

Abstract: An emotion recognition system for assessing human emotional behavior from communication by a speaker includes a processing system configured to receive signals representative of the verbal and/or non-verbal communication. The processing system derives signal features from the received signals. The processing system is further configured to implement at least one intermediate mapping between the signal features and one or more elements of an emotional ontology in order to perform an emotion recognition decision. The emotional ontology provides a gradient representation of the human emotional behavior.

Exploring social annotations for the semantic web

Abstract: In order to obtain a machine understandable semantics for web resources, research on the Semantic Web tries to annotate web resources with concepts and relations from explicitly defined formal ontologies. This kind of formal annotation is usually done manually or semi-automatically. In this paper, we explore a complement approach that focuses on the "social annotations of the web" which are annotations manually made by normal web users without a pre-defined formal ontology. Compared to the formal annotations, although social annotations are coarse-grained, informal and vague, they are also more accessible to more people and better reflect the web resources' meaning from the users' point of views during their actual usage of the web resources. Using a social bookmark service as an example, we show how emergent semantics [2] can be statistically derived from the social annotations. Furthermore, we apply the derived emergent semantics to discover and search shared web bookmarks. The initial evaluation on our implementation shows that our method can effectively discover semantically related web bookmarks that current social bookmark service can not discover easily.

Method and apparatus for building an intelligent automated assistant

Abstract: A method and apparatus are provided for building an intelligent automated assistant. Embodiments of the present invention rely on the concept of “active ontologies” (e.g., execution environments constructed in an ontology-like manner) to build and run applications for use by intelligent automated assistants. In one specific embodiment, a method for building an automated assistant includes interfacing a service-oriented architecture that includes a plurality of remote services to an active ontology, where the active ontology includes at least one active processing element that models a domain. At least one of the remote services is then registered for use in the domain.

Bio-ontologies: current trends and future directions

Abstract: In recent years, as a knowledge-based discipline, bioinformatics has been made more computationally amenable. After its beginnings as a technology advocated by computer scientists to overcome problems of heterogeneity, ontology has been taken up by biologists themselves as a means to consistently annotate features from genotype to phenotype. In medical informatics, artifacts called ontologies have been used for a longer period of time to produce controlled lexicons for coding schemes. In this article, we review the current position in ontologies and how they have become institutionalized within biomedicine. As the field has matured, the much older philosophical aspects of ontology have come into play. With this and the institutionalization of ontology has come greater formality. We review this trend and what benefits it might bring to ontologies and their use within biomedicine.

Automatic fuzzy ontology generation for semantic Web

Abstract: Ontology is an effective conceptualism commonly used for the semantic Web. Fuzzy logic can be incorporated to ontology to represent uncertainty information. Typically, fuzzy ontology is generated from a predefined concept hierarchy. However, to construct a concept hierarchy for a certain domain can be a difficult and tedious task. To tackle this problem, this paper proposes the FOGA (fuzzy ontology generation framework) for automatic generation of fuzzy ontology on uncertainty information. The FOGA framework comprises the following components: fuzzy formal concept analysis, concept hierarchy generation, and fuzzy ontology generation. We also discuss approximating reasoning for incremental enrichment of the ontology with new upcoming data. Finally, a fuzzy-based technique for integrating other attributes of database to the ontology is proposed

Inducing Ontology from Flickr Tags

Abstract: paper, we describe some promising initial results in inducing ontology from the Flickr tag vocabulary, using a subsumption-based model. We describe the utility of faceted ontology as a supplement to a tagging system and present our model and results. We propose a revised, probabilistic model using seed ontologies to induce faceted ontology, and describe how the model can integrate into the logistics of tagging communities.

Building up and reasoning about architectural knowledge

Abstract: Architectural knowledge consists of architecture design as well as the design decisions, assumptions, context, and other factors that together determine why a particular solution is the way it is. Except for the architecture design part, most of the architectural knowledge usually remains hidden, tacit in the heads of the architects. We conjecture that an explicit representation of architectural knowledge is helpful for building and evolving quality systems. If we had a repository of architectural knowledge for a system, what would it ideally contain, how would we build it, and exploit it in practice? In this paper we describe a use-case model for an architectural knowledge base, together with its underlying ontology. We present a small case study in which we model available architectural knowledge in a commercial tool, the Aduna Cluster Map Viewer, which is aimed at ontology-based visualization. Putting together ontologies, use cases and tool support, we are able to reason about which types of architecting tasks can be supported, and how this can be done.

SemSearch: a search engine for the semantic web

Abstract: Existing semantic search tools have been primarily designed to enhance the performance of traditional search technologies but with little support for ordinary end users who are not necessarily familiar with domain specific semantic data, ontologies, or SQL-like query languages. This paper presents SemSearch, a search engine, which pays special attention to this issue by providing several means to hide the complexity of semantic search from end users and thus make it easy to use and effective.

Modelling ontology evaluation and validation

Abstract: We present a comprehensive approach to ontology evaluation and validation, which have become a crucial problem for the development of semantic technologies. Existing evaluation methods are integrated into one sigle framework by means of a formal model. This model consists, firstly, of a meta-ontology called O2, that characterises ontologies as semiotic objects. Based on O2 and an analysis of existing methodologies, we identify three main types of measures for evaluation: structural measures, that are typical of ontologies represented as graphs; functional measures, that are related to the intended use of an ontology and of its components; and usability-profiling measures, that depend on the level of annotation of the considered ontology. The meta-ontology is then complemented with an ontology of ontology validation called oQual, which provides the means to devise the best set of criteria for choosing an ontology over others in the context of a given project. Finally, we provide a small example of how to apply oQual-derived criteria to a validation case.

MASON: A Proposal For An Ontology Of Manufacturing Domain

Abstract: This paper presents a proposal for a manufacturing upper ontology, aimed to draft a common semantic net in manufacturing domain. Usefulness of ontologies for data formalization and sharing, especially in a manufacturing environment, are first discussed. Details are given about the Web Ontology Language (OWL) and its adequation for ontologies in the manufacturing systems is shown. A concrete proposal named MASON (MAnufacturing’s Semantics ONtology) is presented and two applications of this ontology are exposed: automatic cost estimation and semantic-aware multiagent system for manufacturing.

Applications of Ontologies in Software Engineering

Abstract: The emerging field of semantic web technologies promises new stimulus for Software Engineering research. However, since the underlying concepts of the semantic web have a long tradition in the knowledge engineering field, it is sometimes hard for software engineers to overlook the variety of ontology-enabled approaches to Software Engineering. In this paper we therefore present some examples of ontology applications throughout the Software Engineering lifecycle. We discuss the advantages of ontologies in each case and provide a framework for classifying the usage of ontologies in Software Engineering.

Web ontology segmentation: analysis, classification and use

Abstract: Ontologies are at the heart of the semantic web. They define the concepts and relationships that make global interoperability possible. However, as these ontologies grow in size they become more and more difficult to create, use, understand, maintain, transform and classify. We present and evaluate several algorithms for extracting relevant segments out of large description logic ontologies for the purposes of increasing tractability for both humans and computers. The segments are not mere fragments, but stand alone as ontologies in their own right. This technique takes advantage of the detailed semantics captured within an OWL ontology to produce highly relevant segments. The research was evaluated using the GALEN ontology of medical terms and procedures.

Ontology Alignment: Bridging the Semantic Gap

Abstract: This book introduces novel methods and approaches for semantic integration. In addition to developing ground-breaking new methods for ontology alignment, the author provides extensive explanations of up-to-date case studies. It includes a thorough investigation of the foundations and provides pointers to future steps in ontology alignment with conclusion linking this work to the knowledge society.

Gene set enrichment analysis with topGO

Abstract: When the topGO package is loaded three new environments GOBPTerm, GOMFTerm and GOMFTerm are created and binded to the package environment. These environments are build based on the GOTERM environment from package GO. They are used for fast recovering of the information specific to each ontology. In order to access all GO groups that belong to a specific ontology, e.g. Biological Process (BP), one can type:

Ontology-based assembly design and information sharing for collaborative product development

Abstract: To realize a truly collaborative product design and development process, effective communication among design collaborators is a must. In other words, the design intent that is imposed in a product design should be seized and interpreted properly; heterogeneous modeling terms should be semantically processed both by design collaborators and intelligent systems. Ontologies in the Semantic Web can explicitly represent semantics and promote integrated and consistent access to data and services. Thus, if an ontology is used in a heterogeneous and distributed design collaboration, it will explicitly and persistently represent engineering relations that are imposed in an assembly design. Design intent can be captured by reasoning, and, in turn, as reasoned facts, it can be propagated and shared with design collaborators. This paper presents a new paradigm of ontology-based assembly design. In the framework, an assembly design (AsD) ontology serves as a formal, explicit specification of assembly design so that it makes assembly knowledge both machine-interpretable and to be shared. An Assembly Relation Model (ARM) is enhanced using ontologies that represent engineering, spatial, assembly, and joining relations of assembly in a way that promotes collaborative assembly information-sharing environments. In the developed AsD ontology, implicit AsD constraints are explicitly represented using OWL (Web Ontology Language) and SWRL (Semantic Web Rule Language). This paper shows that the ability of the AsD ontology to be reasoned can capture both assembly and joining intents by a demonstration with a realistic mechanical assembly. Finally, this paper presents a new assembly design information-sharing framework and an assembly design browser for a collaborative product development.

Reengineering Thesauri for New Applications: the AGROVOC Example

Abstract: Existing classification schemes and thesauri are lacking in well-defined semantics and structural consistency. Empowering end users in searching collections of ever increasing magnitudes with performance far exceeding plain free-text searching (as used in many Web search engines), and developing systems that not only find but also process information for action, requires far more powerful and complex knowledge organization systems (KOSs). The paper presents a conceptual structure and transition procedure to support the shift from a traditional KOS towards a full-fledged and semantically rich KOS. The proposed structure also complies with other interoperability approaches like RDFS and XML in the Web environment. AGROVOC, a traditional thesaurus developed and maintained by the Food and Agriculture Organization (FAO) of the United Nations, serves as a case study for exploring the reengineering of a traditional thesaurus into a fully-fledged ontology. We start the process of developing an inventory of specific relationship types with well-defined semantics for the agricultural domain and explore the rules-as-you-go approach to streamlining the reengineering process.

A qos-aware selection model for semantic web services

Abstract: Automating Service Oriented Architectures by augmenting them with semantics will form the basis of the next generation of computing. Selection of service still is an important challenge, especially, when a set of services fulfilling user's capabilities requirements have been discovered, among these services which one will be eventually invoked by user is very critical, generally depending on a combined evaluation of qualities of services (Qos). This paper proposes a QoS-based selection of services. Initially we specify a QoS ontology and its vocabulary using the Web Services Modeling Ontology (WSMO) for annotating service descriptions with QoS data. We continue by defining quality attributes and their respective measurements along with a QoS selection model. Finally, we present a fair and dynamic selection mechanism, using an optimum normalization algorithm.

Towards a complete OWL ontology benchmark

Abstract: Aiming to build a complete benchmark for better evaluation of existing ontology systems, we extend the well-known Lehigh University Benchmark in terms of inference and scalability testing. The extended benchmark, named University Ontology Benchmark (UOBM), includes both OWL Lite and OWL DL ontologies covering a complete set of OWL Lite and DL constructs, respectively. We also add necessary properties to construct effective instance links and improve instance generation methods to make the scalability testing more convincing. Several well-known ontology systems are evaluated on the extended benchmark and detailed discussions on both existing ontology systems and future benchmark development are presented.

Information Retrieval by Semantic Similarity

Abstract: Semantic Similarity relates to computing the similarity between conceptually similar but not necessarily lexically similar terms. Typically, semantic similarity is computed by mapping terms to an ontology and by examining their relationships in that ontology. We investigate approaches to computing the semantic similarity between natural language terms (using WordNet as the underlying reference ontology) and between medical terms (using the MeSH ontology of medical and biomedical terms). The most popular semantic similarity methods are implemented and evaluated using WordNet and MeSH. Building upon semantic similarity, we propose the Semantic Similarity based Retrieval Model (SSRM), a novel information retrieval method capable for discovering similarities between documents containing conceptually similar terms. The most effective semantic similarity method is implemented into SSRM. SSRM has been applied in retrieval on OHSUMED (a standard TREC collection available on the Web). The experimental results demonstrated promising performance improvements over classic information retrieval methods utilizing plain lexical matching (e.g., Vector Space Model) and also over state-of-the-art semantic similarity retrieval methods utilizing ontologies.

OWL: Representing Information Using the Web Ontology Language

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A framework for ontology evolution in collaborative environments

Abstract: With the wider use of ontologies in the Semantic Web and as part of production systems, multiple scenarios for ontology maintenance and evolution are emerging. For example, successive ontology versions can be posted on the (Semantic) Web, with users discovering the new versions serendipitously; ontology-development in a collaborative environment can be synchronous or asynchronous; managers of projects may exercise quality control, examining changes from previous baseline versions and accepting or rejecting them before a new baseline is published, and so on. In this paper, we present different scenarios for ontology maintenance and evolution that we have encountered in our own projects and in those of our collaborators. We define several features that categorize these scenarios. For each scenario, we discuss the high-level tasks that an editing environment must support. We then present a unified comprehensive set of tools to support different scenarios in a single framework, allowing users to switch between different modes easily.

Did I damage my ontology? A case for conservative extensions in description logic

Abstract: In computer science, ontologies are dynamic entities: to adapt them to new and evolving applications, it is necessary to frequently perform modifications such as the extension with new axioms and merging with other ontologies. We argue that, after performing such modifications, it is important to know whether the resulting ontology is a conservative extension of the original one. If this is not the case, then there may be unexpected consequences when using the modified ontology in place of the original one in applications. In this paper, we propose and investigate new reasoning problems based on the notion of conservative extension, assuming that ontologies are formulated as TBoxes in the description logic ALC. We show that the fundamental such reasoning problems are decidable and 2EXPTIME-complete. Additionally, we perform a finer-grained analysis that distinguishes between the size of the original ontology and the size of the additional axioms. In particular, we show that there are algorithms whose runtime is 'only' exponential in the size of the original ontology, but double exponential in the size of the added axioms. If the size of the new axioms is small compared to the size of the ontology, these algorithms are thus not significantly more complex than the standard reasoning services implemented in modern description logic reasoners. If the extension of an ontology is not conservative, our algorithm is capable of computing a concept that witnesses non-conservativeness. We show that the computed concepts are of (worst-case) minimal size.

Introducing the Arabic WordNet project

Abstract: Arabic is the official language of hundreds of millions of people in twenty Middle East and northern African countries, and is the religious language of all Muslims of various ethnicities around the world. Surprisingly little has been done in the field of computerised language and lexical resources. It is therefore motivating to develop an Arabic (WordNet) lexical resource that discovers the richness of Arabic as described in Elkateb (2005). This paper describes our approach towards building a lexical resource in Standard Arabic. Arabic WordNet (AWN) will be based on the design and contents of the universally accepted Princeton WordNet (PWN) and will be mappable straightforwardly onto PWN 2.0 and EuroWordNet (EWN), enabling translation on the lexical level to English and dozens of other languages. Several tools specific to this task will be developed. AWN will be a linguistic resource with a deep formal semantic foundation. Besides the standard wordnet representation of senses, word meanings are defined with a machine understandable semantics in first order logic. The basis for this semantics is the Suggested Upper Merged Ontology (SUMO) and its associated domain ontologies. We will greatly extend the ontology and its set of mappings to provide formal terms and definitions equivalent to each synset.

Semantic web services in factory automation: fundamental insights and research roadmap

Abstract: One of the significant challenges for current and future manufacturing systems is that of providing rapid reconfigurability in order to evolve and adapt to mass customization. This challenge is aggravated if new types of processes and components are introduced, as existing components are expected to interact with the novel entities but have no previous knowledge on how to collaborate. This statement not only applies to innovative processes and devices, but is also due to the impossibility to incorporate knowledge in a single device about all types of available system components. This paper proposes the use of Semantic Web Services in order to overcome this challenge. The use of ontologies and explicit semantics enable performing logical reasoning to infer sufficient knowledge on the classification of processes that machines offer, and on how to execute and compose those processes to carry out manufacturing orchestration autonomously. A series of motivating utilization scenarios are illustrated, and a research roadmap is presented.