Towards Context Driven Modularization of Large Biomedical Ontologies

Formal knowledge about human anatomy, radiology or diseases is necessary to support clinical applications such as medical image search. This machine processable knowledge can be acquired from biomedical domain ontologies, which however, are typically very large and complex models. Thus, their straightforward incorporation into the software applications becomes difficult. In this paper we discuss first ideas on a statistical approach for modularizing large medical ontologies and we prioritize the practical applicability aspect. The underlying assumption is that the application relevant ontology fragments, i.e. modules, can be identified by the statistical analysis of the ontology concepts in the domain corpus. Accordingly, we argue that most frequently occurring concepts in the domain corpus define the application context and can therefore potentially yield the relevant ontology modules. We illustrate our approach on an example case that involves a large ontology on human anatomy and report on our first manual experiments

Ontology construction from online ontologies

One of the main hurdles towards a wide endorsement of ontologies is the high cost of constructing them. Reuse of existing ontologies offers a much cheaper alternative than building new ones from scratch, yet tools to support such reuse are still in their infancy. However, more ontologies are becoming available on the web, and online libraries for storing and indexing ontologies are increasing in number and demand. Search engines have also started to appear, to facilitate search and retrieval of online ontologies. This paper presents a fresh view on constructing ontologies automatically, by identifying, ranking, and merging fragments of online ontologies

The modular structure of an ontology: Atomic decomposition

Extracting a subset of a given ontology that captures all the ontology’s knowledge about a specified set of terms is a well-understood task. This task can be based, for instance, on locality-based modules. However, a single module does not allow us to understand neither topicality, connectedness, structure, or superfluous parts of an ontology, nor agreement between actual and intended modeling. The strong logical properties of locality-based modules suggest that the family of all such modules of an ontology can support comprehension of the ontology as a whole. However, extracting that family is not feasible, since the number of localitybased modules of an ontology can be exponential w.r.t. its size. In this paper we report on a new approach that enables us to efficiently extract a polynomial representation of the family of all locality-based modules of an ontology. We also describe the fundamental algorithm to pursue this task, and report on experiments carried out and results obtained.

Winnowing ontologies based on application use

The requirements of specific applications and services are often over estimated when ontologies are reused or built. This sometimes results in many ontologies being too large for their intended purposes. It is not uncommon that when applications and services are deployed over an ontology, only a few parts of the ontology are queried and used. Identifying which parts of an ontology are being used could be helpful to winnow the ontology, i.e., simplify or shrink the ontology to smaller, more fit for purpose size. Some approaches to handle this problem have already been suggested in the literature. However, none of that work showed how ontology-based applications can be used in the ontology-resizing process, or how they might be affected by it. This paper presents a study on the use of the AKT Reference Ontology by a number of applications and services,and investigates the possibility of relying on this usage information to winnow that ontology

Measuring Inconsistencies Propagation from Change Operation Based on Ontology Partitioning

International audienceInconsistency measure is an activity related to the ontology evolution. Being a coherent entity, an ontology must change and a modification operation in ontology could generate inconsistencies in its other parts. It is then important to measure these inconsistencies and follow the impact propagation. In this paper, we propose an inconsistency measure of an ontological change and its propagation effects on the other entities of the ontology. The measure is based on the weight of the dependencies between concepts in a community. Ontology is divided into communities which are a set of concepts that have preferential relations. To follow the impact propagation, we propose a process that uses the Change-and-Fix' approach to mark the impacted entities

Application of User Profiling on Ontology Module Extraction for Medical portals

One fit all for approach for searching and ranking discovered knowledge on the Internet does not cater for the diverse variety of users and user groups with different preferences, information needs and priorities. This is of a particular case in the National electronic Library of Infection in the UK (NeLI, www.neli.org.uk) accessed by a number of medical professionals with different preferences and medical information needs. We define personal and group profiles, based on user-specified interests, and develop an ontology module extraction service defining the key area of the infection ontology of a particular relevance to each user group. In this paper we discuss how ontology modularisation can improve the NeLI portal by providing customised alert, recommender service and specialitycustomised browsing tree structure

Ontology summarization: an analysis and an evaluation

Ontology summarization has been recognized as a very useful technique to facilitate ontology understanding and then support ontology reuse as a new or supplementing technique. A number of efforts have emerged lately that apply different criteria, addressing different features of ontology, to extract ontology summaries. However, those efforts are ad-hoc in that there lacks consensus on a number of issues fundamental to the development of the field, such as a definition for ontology summarization, use case scenarios etc. Also, there lack sufficient evaluations and analysis, e.g. comparison among them and with other similar techniques, to provide meaning guidelines for users of this technique. With the aim to provide solutions to those fundamental issues, in this work, we present an analysis of this technique and its approaches. With the help of an objective evaluation method, we investigate what features of ontology are important in ontology summarization

Knowledgebase Representation for Royal Bengal Tiger In The Context of Bangladesh

Royal Bengal Tiger is one of the penetrating threaten animal in Bangladesh forest at Sundarbans. In this work we have had concentrate to establish a robust Knowledgebase for Royal Bengal Tiger. We improve our previous work to achieve efficiency on knowledgebase representation. We have categorized the tigers from others animal from collected data by using Support Vector Machines(SVM) .Manipulating our collected data in a structured way by XML parsing on JAVA platform. Our proposed system generates n-triple by considering parsed data. We proceed on an ontology is constructed by ProtE9;gE9; which containing information about names, places, awards. A straightforward approach of this work to make the knowledgebase representation of Royal Bengal Tiger more reliable on the web. Our experiments show the effectiveness of knowledgebase construction. Complete knowledgebase construction of Royal Bengal Tigers how the efficient out-put. The complete knowledgebase construction helps to integrate the raw data in a structured way. The outcome of our proposed system contains the complete knowledgebase. Our experimental results show the strength of our system by retrieving information from ontology in reliable way