Search (67 results, page 1 of 4)

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Abstract

On the Semantic Web, the types of resources and the semantic relationships between resources are defined in an ontology. By using that information, the accuracy of information retrieval can be improved. In this paper, we present effective ranking and search techniques considering the semantic relationships in an ontology. Our technique retrieves top-k resources which are the most relevant to query keywords through the semantic relationships. To do this, we propose a weighting measure for the semantic relationship. Based on this measure, we propose a novel ranking method which considers the number of meaningful semantic relationships between a resource and keywords as well as the coverage and discriminating power of keywords. In order to improve the efficiency of the search, we prune the unnecessary search space using the length and weight thresholds of the semantic relationship path. In addition, we exploit Threshold Algorithm based on an extended inverted index to answer top-k results efficiently. The experimental results using real data sets demonstrate that our retrieval method using the semantic information generates accurate results efficiently compared to the traditional methods.

Source

Information processing and management. 50(2014) no.1, S.132-155

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Abstract

Search has been and will continue to be an important tool for users who need to locate information in an ever increasing mount of resources. Not all queries have a well defined information need that can easily be described by a keyword query. Exploratory search is one such type of search where the user is not necessarily proficient in the domain or does not have a clear idea of what he is looking for. In such types of search, navigation is beneficial to guide the user in his quest. In this paper we present an approach to contextual navigation search, based on a hierarchical structure constructed from folksonomy tags. The tags are associated with an extended semantic representation used to guide the navigation. Five semantic navigators are introduced, which are navigation strategies the user can benefit from. We present a prototype which has been implemented to show the applicability of the approach to the problem at hand. The preliminary results are promising and demonstrate the ability to direct the user at interesting navigational suggestions and documents.

Source

I-KNOW '11: Proceedings of the 11th International Conference on Knowledge Management and Knowledge Technologies, Article 34

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Source

Information processing and management. 48(2012) no.3, S.399-418

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Abstract

Considering the characteristics of hypertext systems and problems such as cognitive overload and the disorientation of users, this project studies subject hypertext documents that have undergone conceptual structuring using facets for content representation and improvement of information retrieval during navigation. The main objective was to assess the possibility of the application of topic map technology for automating the compatibilization process of these structures. For this purpose, two dissertations from the UFMG Information Science Post-Graduation Program were adopted as samples. Both dissertations had been duly analyzed and structured on the MHTX (Hypertextual Map) prototype database. The faceted structures of both dissertations, which had been represented in conceptual maps, were then converted into topic maps. It was then possible to use the merge property of the topic maps to promote the semantic interrelationship between the maps and, consequently, between the hypertextual information resources proper. The merge results were then analyzed in the light of theories dealing with the compatibilization of languages developed within the realm of information technology and librarianship from the 1960s on. The main goals accomplished were: (a) the detailed conceptualization of the merge process of the topic maps, considering the possible compatibilization levels and the applicability of this technology in the integration of faceted structures; and (b) the production of a detailed sequence of steps that may be used in the implementation of topic maps based on faceted structures.

Date

22. 2.2013 11:39:23

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Abstract

Major efforts have been conducted on ontology learning, that is, semiautomatic processes for the construction of domain ontologies from diverse sources of information. In the past few years, a research trend has focused on the construction of educational ontologies, that is, ontologies to be used for educational purposes. The identification of the terminology is crucial to build ontologies. Term extraction techniques allow the identification of the domain-related terms from electronic resources. This paper presents LiTeWi, a novel method that combines current unsupervised term extraction approaches for creating educational ontologies for technology supported learning systems from electronic textbooks. LiTeWi uses Wikipedia as an additional information source. Wikipedia contains more than 30 million articles covering the terminology of nearly every domain in 288 languages, which makes it an appropriate generic corpus for term extraction. Furthermore, given that its content is available in several languages, it promotes both domain and language independence. LiTeWi is aimed at being used by teachers, who usually develop their didactic material from textbooks. To evaluate its performance, LiTeWi was tuned up using a textbook on object oriented programming and then tested with two textbooks of different domains-astronomy and molecular biology.

Date

22. 1.2016 12:38:14

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Abstract

Astronomy, like many domains, already has several sets of terminology in general use, referred to as controlled vocabularies. For example, the keywords for tagging journal articles, or the taxonomy of terms used to label image files. These existing vocabularies can be encoded into skos, a W3C proposed recommendation for representing vocabularies on the Semantic Web, so that computer systems can help users to search for and discover resources tagged with vocabulary concepts. However, this requires a search mechanism to go from a user-supplied string to a vocabulary concept. In this paper, we present our experiences in implementing the Vocabulary Explorer, a vocabulary search service based on the Terrier Information Retrieval Platform. We investigate the capabilities of existing document weighting models for identifying the correct vocabulary concept for a query. Due to the highly structured nature of a skos encoded vocabulary, we investigate the effects of term weighting (boosting the score of concepts that match on particular fields of a vocabulary concept), and query expansion. We found that the existing document weighting models provided very high quality results, but these could be improved further with the use of term weighting that makes use of the semantic evidence.

Source

Information processing and management. 46(2010) no.4, S.470-478

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Abstract

In this paper, we focus on applying sentiment analysis to resources from online art collections, by exploiting, as information source, tags intended as textual traces that visitors leave to comment artworks on social platforms. We present a framework where methods and tools from a set of disciplines, ranging from Semantic and Social Web to Natural Language Processing, provide us the building blocks for creating a semantic social space to organize artworks according to an ontology of emotions. The ontology is inspired by the Plutchik's circumplex model, a well-founded psychological model of human emotions. Users can be involved in the creation of the emotional space, through a graphical interactive interface. The development of such semantic space enables new ways of accessing and exploring art collections. The affective categorization model and the emotion detection output are encoded into W3C ontology languages. This gives us the twofold advantage to enable tractable reasoning on detected emotions and related artworks, and to foster the interoperability and integration of tools developed in the Semantic Web and Linked Data community. The proposal has been evaluated against a real-word case study, a dataset of tagged multimedia artworks from the ArsMeteo Italian online collection, and validated through a user study.

Source

Information processing and management. 52(2016) no.1, S.139-162

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Abstract

Personalized search is aimed at tailoring the search outcome to users; to this aim user profiles play an important role: the more faithfully a user profile represents the user interests and preferences, the higher is the probability to improve the search process. In the approaches proposed in the literature, user profiles are formally represented as bags of words, as vectors, or as conceptual taxonomies, generally defined based on external knowledge resources (such as the WordNet and the ODP - Open Directory Project). Ontologies have been more recently considered as a powerful expressive means for knowledge representation. The advantage offered by ontological languages is that they allow a more structured and expressive knowledge representation with respect to the above mentioned approaches. A challenging research activity consists in defining user profiles by a knowledge extraction process from an existing ontology, with the main aim of producing a semantically rich representation of the user interests. In this paper a method to automatically define a personal ontology via a knowledge extraction process from the general purpose ontology YAGO is presented; starting from a set of keywords, which are representatives of the user interests, the process is aimed to define a structured and semantically coherent representation of the user topical interests. In the paper the proposed method is described, as well as some evaluations that show its effectiveness.

Source

Information processing and management. 49(2013) no.3, S.640-658

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Abstract

A method to develop a prototype domain ontology has been described. The domain selected for the study is Accelerator Driven Systems. This is a multidisciplinary and interdisciplinary subject comprising Nuclear Physics, Nuclear and Reactor Engineering, Reactor Fuels and Radioactive Waste Management. Since Accelerator Driven Systems is a vast topic, select areas in it were singled out for the study. Both qualitative and quantitative methods such as Content analysis, Facet analysis and Clustering were used, to develop the web-based model.

Date

22. 7.2010 19:41:16

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Content

Vgl.: https%3A%2F%2Faclanthology.org%2FD19-5317.pdf&usg=AOvVaw0ZZFyq5wWTtNTvNkrvjlGA.

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Abstract

Purpose - This paper sets out to discuss the use of information extraction (IE), a natural language-processing (NLP) technique to assist "rich" semantic indexing of diverse archaeological text resources. The focus of the research is to direct a semantic-aware "rich" indexing of diverse natural language resources with properties capable of satisfying information retrieval from online publications and datasets associated with the Semantic Technologies for Archaeological Resources (STAR) project. Design/methodology/approach - The paper proposes use of the English Heritage extension (CRM-EH) of the standard core ontology in cultural heritage, CIDOC CRM, and exploitation of domain thesauri resources for driving and enhancing an Ontology-Oriented Information Extraction process. The process of semantic indexing is based on a rule-based Information Extraction technique, which is facilitated by the General Architecture of Text Engineering (GATE) toolkit and expressed by Java Annotation Pattern Engine (JAPE) rules. Findings - Initial results suggest that the combination of information extraction with knowledge resources and standard conceptual models is capable of supporting semantic-aware term indexing. Additional efforts are required for further exploitation of the technique and adoption of formal evaluation methods for assessing the performance of the method in measurable terms. Originality/value - The value of the paper lies in the semantic indexing of 535 unpublished online documents often referred to as "Grey Literature", from the Archaeological Data Service OASIS corpus (Online AccesS to the Index of archaeological investigationS), with respect to the CRM ontological concepts E49.Time Appellation and P19.Physical Object.

Footnote

Beitrag in einem Special Issue: Content architecture: exploiting and managing diverse resources: proceedings of the first national conference of the United Kingdom chapter of the International Society for Knowedge Organization (ISKO)

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Date

20. 1.2015 18:30:22

Source

Aslib journal of information management. 68(2016) no.1, S.99-111

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Abstract

Knowledge tends to be structured differently in different types of information resources and information genres due to the different purposes of the resource/genre, and the characteristics of the media or format of the resource. This study investigates subject organization in three types of information resources: books (i.e. monographs), Web directories and information websites that provide information on particular subjects. Twelve subjects (topics) were selected in the areas of science, arts/humanities and social science, and two books, two Web directories and two information websites were sampled for each subject. The top two levels of the hierarchical subject organization in each resource were harvested and analyzed. Books have the highest proportion of general subject categories (e.g. history, theory and definition) and process categories (indicating step-by-step instructions). Information websites have the highest proportion of target user categories and genre-specific categories (e.g. about us and contact us), whereas Web directories have the highest proportion of specialty categories (i.e. sub-disciplines), industry-role categories (e.g. stores, schools and associations) and format categories (e.g. books, blogs and videos). Some disciplinary differences were also identified.

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Date

20. 1.2015 18:30:22

Source

Aslib journal of information management. 66(2014) no.5, S.494-518

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Abstract

The article presents a method for automatic semantic indexing of archaeological grey-literature reports using empirical (rule-based) Information Extraction techniques in combination with domain-specific knowledge organization systems. The semantic annotation system (OPTIMA) performs the tasks of Named Entity Recognition, Relation Extraction, Negation Detection, and Word-Sense Disambiguation using hand-crafted rules and terminological resources for associating contextual abstractions with classes of the standard ontology CIDOC Conceptual Reference Model (CRM) for cultural heritage and its archaeological extension, CRM-EH. Relation Extraction (RE) performance benefits from a syntactic-based definition of RE patterns derived from domain oriented corpus analysis. The evaluation also shows clear benefit in the use of assistive natural language processing (NLP) modules relating to Word-Sense Disambiguation, Negation Detection, and Noun Phrase Validation, together with controlled thesaurus expansion. The semantic indexing results demonstrate the capacity of rule-based Information Extraction techniques to deliver interoperable semantic abstractions (semantic annotations) with respect to the CIDOC CRM and archaeological thesauri. Major contributions include recognition of relevant entities using shallow parsing NLP techniques driven by a complimentary use of ontological and terminological domain resources and empirical derivation of context-driven RE rules for the recognition of semantic relationships from phrases of unstructured text.

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Abstract

In order to improve the organization of classical music information resources, we constructed a classical music recording ontology, on top of which we then designed an online classical music catalog. Our construction of the classical music recording ontology consisted of three steps: identifying the purpose, analyzing the ontology, and encoding the ontology. We identified the main classes and properties of the domain by investigating classical music recording resources and users' information needs. We implemented the ontology in the Web Ontology Language (OWL) using five steps: transforming the properties, encoding the transformed properties, defining ranges of the properties, constructing individuals, and standardizing the ontology. In constructing the online catalog, we first designed the structure and functions of the catalog based on investigations into users' information needs and information-seeking behaviors. Then we extracted classes and properties of the ontology using the Apache Jena application programming interface (API), and constructed a catalog in the Java environment. The catalog provides a hierarchical main page (built using the Functional Requirements for Bibliographic Records (FRBR) model), a classical music information network and integrated information service; this combination of features greatly eases the task of finding classical music recordings and more information about classical music.

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Abstract

This paper presents a Graph Inference retrieval model that integrates structured knowledge resources, statistical information retrieval methods and inference in a unified framework. Key components of the model are a graph-based representation of the corpus and retrieval driven by an inference mechanism achieved as a traversal over the graph. The model is proposed to tackle the semantic gap problem-the mismatch between the raw data and the way a human being interprets it. We break down the semantic gap problem into five core issues, each requiring a specific type of inference in order to be overcome. Our model and evaluation is applied to the medical domain because search within this domain is particularly challenging and, as we show, often requires inference. In addition, this domain features both structured knowledge resources as well as unstructured text. Our evaluation shows that inference can be effective, retrieving many new relevant documents that are not retrieved by state-of-the-art information retrieval models. We show that many retrieved documents were not pooled by keyword-based search methods, prompting us to perform additional relevance assessment on these new documents. A third of the newly retrieved documents judged were found to be relevant. Our analysis provides a thorough understanding of when and how to apply inference for retrieval, including a categorisation of queries according to the effect of inference. The inference mechanism promoted recall by retrieving new relevant documents not found by previous keyword-based approaches. In addition, it promoted precision by an effective reranking of documents. When inference is used, performance gains can generally be expected on hard queries. However, inference should not be applied universally: for easy, unambiguous queries and queries with few relevant documents, inference did adversely affect effectiveness. These conclusions reflect the fact that for retrieval as inference to be effective, a careful balancing act is involved. Finally, although the Graph Inference model is developed and applied to medical search, it is a general retrieval model applicable to other areas such as web search, where an emerging research trend is to utilise structured knowledge resources for more effective semantic search.

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Date

20. 1.2015 18:30:22

Source

Aslib journal of information management. 66(2014) no.6, S.678-696

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Abstract

This article comprises a literature review and conceptual analysis of Topic Maps-the ISO standard for representing information about the structure of information resources-according to the principles of Knowledge Organization (KO). Using the main principles from this discipline, the study shows how Topic Maps is proposed as an ontology model independent of technology. Topic Maps constitutes a 'bibliographic' meta-language able to represent, extend, and integrate almost all existing Knowledge Organization Systems (KOS) in a standards-based generic model applicable to digital content and to the Web. This report also presents an inventory of the current applications of Topic Maps in Libraries, Archives, and Museums (LAM), as well as in the Digital Humanities. Finally, some directions for further research are suggested, which relate Topic Maps to the main research trends in KO.

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Abstract

How information resources can be meaningfully related has been addressed in contexts from bibliographic entries to hyperlinks and, more recently, linked data. The genre structure and relationships among genre structure constituents shed new light on organizing information by purpose or function. This study examines the relationships among a set of functional units previously constructed in a taxonomy, each of which is a chunk of information embedded in a document and is distinct in terms of its communicative function. Through a card-sort study, relationships among functional units were identified with regard to their occurrence and function. The findings suggest that a group of functional units can be identified, collocated, and navigated by particular relationships. Understanding how functional units are related to each other is significant in linking information pieces in documents to support finding, aggregating, and navigating information in a distributed information environment.