MOWL: An ontology representation language for web-based multimedia applications
27 Dec 2013-ACM Transactions on Multimedia Computing, Communications, and Applications (ACM)-Vol. 10, Iss: 1, pp 8
TL;DR: A new perceptual modeling technique for reasoning with media properties observed in multimedia instances and the latent concepts is proposed, and a probabilistic reasoning scheme for belief propagation across domain concepts through observation of media properties is introduced.
Abstract: Several multimedia applications need to reason with concepts and their media properties in specific domain contexts. Media properties of concepts exhibit some unique characteristics that cannot be dealt with conceptual modeling schemes followed in the existing ontology representation and reasoning schemes. We have proposed a new perceptual modeling technique for reasoning with media properties observed in multimedia instances and the latent concepts. Our knowledge representation scheme uses a causal model of the world where concepts manifest in media properties with uncertainties. We introduce a probabilistic reasoning scheme for belief propagation across domain concepts through observation of media properties. In order to support the perceptual modeling and reasoning paradigm, we propose a new ontology language, Multimedia Web Ontology Language (MOWL). Our primary contribution in this article is to establish the need for the new ontology language and to introduce the semantics of its novel language constructs. We establish the generality of our approach with two disperate knowledge-intensive applications involving reasoning with media properties of concepts.
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01 Apr 2007
TL;DR: Call for papers for Special Issue of ACM Transactions on Multimedia Computing, Communications and Applications on Interactive Digital Television.
Abstract: Call for papers for Special Issue of ACM Transactions on Multimedia Computing, Communications and Applications on Interactive Digital Television
201 citations
17 Nov 2013
TL;DR: A novel method for content-based recommendation of media-rich commodities using probabilistic multimedia ontology that enables interpretation of media based and semantic product features in context of domain concepts is presented.
Abstract: We present a novel method for content-based recommendation of media-rich commodities using probabilistic multimedia ontology. The ontology encodes subjective knowledge of experts that enables interpretation of media based and semantic product features in context of domain concepts. Our recommendation is based on semantic compatibility between the products and user profile in context of use. We use probabilistic knowledge representation and reasoning framework to achieve robust and flexible results. The approach has been validated with fashion preferences of several individuals with a large collection of Sarees, an ethnic dress for women in Indian subcontinent.
24 citations
Cites background or methods from "MOWL: An ontology representation la..."
...An alternate scheme for ontology representation for multimedia applications, Multimedia Web Ontology Language (MOWL) [5], is based on a causal model of the world, where abstract concepts are believed to manifest into specific media properties in multimedia instances....
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...We have used MOWL to encode the domain knowledge, since it supports encoding of media properties of concepts with conditional probabilities and enables reasoning with such media properties....
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...Section II presents a brief introduction to MOWL, the multimedia ontology representation scheme used in the system....
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...We have encoded the ontology using a new ontology language, MOWL [5], that enables the analysis of visual properties of garments with respect to fashion concepts....
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...The reasoning model of MOWL comprises creation of Observation Models (OM’s) from the media property descriptions of related concepts....
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01 Jan 2019
TL;DR: Internet of Things (IoT), the most demanding platform that describes the interconnection of physical devices in near future, needs redesigning the infrastructure so that the production of embedded vehicles can be chained to an embedded traffic management system.
Abstract: Internet of Things (IoT) is the most demanding platform that describes the interconnection of physical devices in near future. Since, the inter-connection of physical devices is getting more popular with the internet day by day, these interlinked devices are capable of integration among themselves in order to operate. Automated vehicles are being produced heavily nowadays and it is considered to be the next technological rage in the field of transportation. This revolution in the transport environment needs redesigning the infrastructure so that the production of embedded vehicles can be chained to an embedded traffic management system. This instinctual design of the traffic control and management system can lead to the improvement of the traffic congestion problem. The traffic density can be calculated using a Raspberry Pi microcomputer and a couple of ultrasonic sensors and the lanes can be operated accordingly. A website can be designed where traffic data can be uploaded and any user can retrieve it. This property will be useful to the users for getting real-time information and detection of any road intersection and discover the fastest traffic route.
19 citations
23 Aug 2017
TL;DR: This paper exhibits a novel context-aware service framework for IoT based Smart Traffic Management using ontology to regulate smooth traffic flow in smart cities by analyzing real-time traffic environment by utilizing contextual information.
Abstract: This paper exhibits a novel context-aware service framework for IoT based Smart Traffic Management using ontology to regulate smooth traffic flow in smart cities by analyzing real-time traffic environment. The proposed approach makes smarter use of transport networks to achieve objectives related to performance of transport system. This requires efficient traffic planning measures which relate to the actions designed to adjust the demand and capacity of the network in time and space by use of IoT technologies. The adoption of sensors and IoT devices in Smart Traffic System helps to capture the user's preferences and context information which can be in the form of travel time, weather conditions or real-life driving patterns. We have employed multimedia ontology to derive higher level descriptions of traffic conditions and vehicles from perceptual observation of traffic information which provides important grounds for our proposed IoT framework. The multimedia ontology encoded in Multimedia Web Ontology Language(MOWL) helps to define classes, properties, and structure of a possible traffic environment to provide insights across the transportation network. MOWL supports Dynamic Bayesian networks (DBN) to deal with time-series data and uncertainties linked with context observations which fits the definition of an intelligent IoT system. Thus, our proposed smart traffic framework aggregates information corresponding to traffic domain such as traffic videos captured using CCTV cameras and allows automatic prediction of dynamically changing situations which helps to make traffic authorities more responsive. We have illustrated use of our approach by utilizing contextual information, to assess real-time congestion situation on roads thus allowing to visualize planning services. Once the congestion situation is predicted, alternate congestion free routes which are in accordance with the coveted criteria are suggested that can be propagated through text-messages or e-mails to the users.
18 citations
Cites background or methods from "MOWL: An ontology representation la..."
...Figure 3 shows the snippet of smart tra c ontology encoded in MOWL. e domain concepts in the gure are represented as oval nodes while their observable media properties are shown as gray boxes. e black straight edges in the ontology (e.g the one connecting VehicleBreakDown to MiserableRoadSituation) denotes the subclass relationship between the concepts and the media properties. e do ed lines represents the domain speci c relations while the transition links are shown in the red color. e values at each link is denoted by the probability pair p (M | C) and p (M |∼ C) where C is a concept and M is a media node....
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...MOWL allows for context-aware data fusion through inference processes to identify the current user context....
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...Figure 10 shows the resulting probabilities for 8 time slices. e probability for MiserableRoadSituation increases till three frames based on evidences - JCB, Car, Rubble, Barrirers, VehilceIssue, VehicleStop which was initially set to (TTTTFF) but as the other evidences come into play, it leads to a rise in probability for VehicleBreakDown continuously till eighth frame based on evidences MiserableRoadSituation and VehilceIssue, VehicleStop, Car set to (FTFFTT). is is what was expected in a real time which illustrates the e ectiveness of utilizing DBN encoded MOWL in smart tra c environments....
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...Addition of the transition links in the MOWL encoded ontology provides...
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...Figure 4 shows a DBN based framework for context-ware data fusion system. e semantics for dynamic situation modeling in MOWL consists of context a ributes at the lowest level, followed by context states and further by situations at di erent time slices....
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IBM1
TL;DR: The main entities of the version 3.1 of the Nested Context Model (NCM) are presented, which concentrate efforts at integrating support for enriched knowledge description to the model, which enables the specification of relationships between knowledge descriptions and multimedia content in the hypermedia way.
Abstract: Most of multimedia documents available today are agnostic to data semantics and their specification language offer little to ease authoring of meaningful content. In this paper, we present the main entities of the version 3.1 of the Nested Context Model (NCM), which concentrate efforts at integrating support for enriched knowledge description to the model. This extension enables the specification of relationships between knowledge descriptions and multimedia content in the hypermedia way, composing what we call hyperknowledge in this paper. NCM previous version (3.0) is a hypermedia conceptual model. NCL (Nested Context Language), which is part of international standards and ITU recommendations, was engineered according to NCM 3.0 definitions. The extensions discussed in this paper contribute not only for advances in the NCL, but mainly as a conceptual model for hyperknowledge document engineering.
14 citations
Cites background from "MOWL: An ontology representation la..."
...The Multimedia Web Ontology Language (MOWL) is an extension of OWL language with features for creating perceptual models of concepts and real-life events to allow reasoning [12]....
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TL;DR: These are the short notes for a two hour tutorial on principles and practice of computer graphics and scientific visualization and they cannot completely replace the contents of the tutorial transparencies and slides since restrictions in space and print quality do not permit the inclusion of figures and example images.
Abstract: These are the short notes for a two hour tutorial on principles and practice of computer graphics and scientific visualization. They are intended to summarize the contents of the tutorial transparencies and slides but they cannot completely replace them since restrictions in space and print quality do not permit the inclusion of figures and example images. For further reference the following standard text should be consulted: [3, 8, 5, 1, 6, 2, 9]
1,869 citations
"MOWL: An ontology representation la..." refers background in this paper
...2The operator ∩∗ denotes the regularized intersection [Foley et al. 1982] and is defined as A∩∗ B = closure(interior(A ∩ B))....
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TL;DR: This paper discusses how the philosophy and features of OWL can be traced back to these older formalisms, with modifications driven by several other constraints on OWL.
1,630 citations
01 Oct 2002
TL;DR: This paper introduces the DOLCE upper level ontology, the first module of a Foundational Ontologies Library being developed within the WonderWeb project, and suggests that such analysis could hopefully lead to an ?
Abstract: In this paper we introduce the DOLCE upper level ontology, the first module of a Foundational Ontologies Library being developed within the WonderWeb project. DOLCE is presented here in an intuitive way; the reader should refer to the project deliverable for a detailed axiomatization. A comparison with WordNet's top-level taxonomy of nouns is also provided, which shows how DOLCE, used in addition to the OntoClean methodology, helps isolating and understanding some major WordNet?s semantic limitations. We suggest that such analysis could hopefully lead to an ?ontologically sweetened? WordNet, meant to be conceptually more rigorous, cognitively transparent, and efficiently exploitable in several applications.
1,100 citations