MPEG-7 Based Image Retrieval on the World Wide Web

Due to the rapid growth of the number of digital media elements like image, video, audio, graphics on Internet, there is an increasing demand for effective search and retrieval techniques. Recently, many search engines have made image search as an option like Google, AlltheWeb, AltaVista, Freenet. In addition to this, Ditto, Picsearch, can search only the images on Internet. There are also other domain specific search engines available for graphics and clip art, audio, video, educational images, artwork, stock photos, science and nature [www.faganfinder.com/img]. These entire search engines are directory based. They crawls the entire Internet and index all the images in certain categories. They do not display the images in any particular order with respect to the time and context. With the availability of MPEG-7, a standard for describing multimedia content, it is now possible to store the images with its metadata in a structured format. This helps in searching and retrieving the images. The MPEG-7 standard uses XML to describe the content of multimedia information objects. These objects will have metadata information in the form of MPEG-7 or any other similar format associated with them. It can be used in different ways to search the objects. In this paper we propose a system, which can do content based image retrieval on the World Wide Web. It displays the result in user-defined order

A multicriteria ant colony algorithm for generating music playlists

In this paper we address the problem of music playlist generation based on the user-personalized specification of context information. We propose a generic semantic multicriteria ant colony algorithm capable of dealing with domain-specific problems by the use of ontologies. It also employs any associated metadata defined in the search space to feed its solution-building process and considers any restrictions the user may have specified. An example is given of the use of the algorithm for the problem of automatic generation of music playlists, some experimental results are presented and the behavior of the approach is explained in different situations. 2011 Elsevier Ltd. All rights reserved.This work has been partially supported by the Spanish Ministry of Education and Science under the funding project CENIT-MIOI CENIT-2008 1019 and by the Microsoft Research Labs (Cambridge) under the "Create, Play and Learn" program.Mocholi Agües, JA.; Martinez Valero, VM.; Jaén Martínez, FJ.; Catalá Bolós, A. (2012). A multicriteria ant colony algorithm for generating music playlists. Expert Systems with Applications. 39(3):2270-2278. doi:10.1016/j.eswa.2011.07.131S2270227839

A System for Audio Personalization with Applications on Wireless Devices

We present and analyze a system for dynamically tailoring discrete audio content for numerous users based on aggregate data and intuitive feedback mechanisms. The framework for this system utilizes a flexible client-server architecture to facilitate audio dissemination, with particular attention to distribution over wireless networks. We discuss the requirements and specifications of such a system. We further analyze the algorithms and protocols required for its operation. Finally, we outline and provide data from a demonstration of this application

Context-based multimedia semantics modelling and representation

The evolution of the World Wide Web, increase in processing power, and more network bandwidth have contributed to the proliferation of digital multimedia data. Since multimedia data has become a critical resource in many organisations, there is an increasing need to gain efficient access to data, in order to share, extract knowledge, and ultimately use the knowledge to inform business decisions. Existing methods for multimedia semantic understanding are limited to the computable low-level features; which raises the question of how to identify and represent the high-level semantic knowledge in multimedia resources.In order to bridge the semantic gap between multimedia low-level features and high-level human perception, this thesis seeks to identify the possible contextual dimensions in multimedia resources to help in semantic understanding and organisation. This thesis investigates the use of contextual knowledge to organise and represent the semantics of multimedia data aimed at efficient and effective multimedia content-based semantic retrieval.A mixed methods research approach incorporating both Design Science Research and Formal Methods for investigation and evaluation was adopted. A critical review of current approaches for multimedia semantic retrieval was undertaken and various shortcomings identified. The objectives for a solution were defined which led to the design, development, and formalisation of a context-based model for multimedia semantic understanding and organisation. The model relies on the identification of different contextual dimensions in multimedia resources to aggregate meaning and facilitate semantic representation, knowledge sharing and reuse. A prototype system for multimedia annotation, CONMAN was built to demonstrate aspects of the model and validate the research hypothesis, H₁.Towards providing richer and clearer semantic representation of multimedia content, the original contributions of this thesis to Information Science include: (a) a novel framework and formalised model for organising and representing the semantics of heterogeneous visual data; and (b) a novel S-Space model that is aimed at visual information semantic organisation and discovery, and forms the foundations for automatic video semantic understanding

Audio Structuring and Personalized Retrieval Using Ontologies

The goal of this work is to improve the accuracy (precision and recall) and communication effectiveness of a database system response to a user information request, by utilizing a domain-specific ontology. This ontology is employed, along with user profile information, to automatically select and deliver appropriate information units from a database. Specifically, the focus here is on multimedia audio databases: we are developing a Personal AudioCast system at the USC Integrated Media Systems Center which creates and delivers to an end-user personalized audio programs constructed from an audio database. Techniques are developed to segment and structure audio information, process user requests to generate custom audio results, create and optimize SQL queries, and present the results to the user. 1

Front Matter - Soft Computing for Data Mining Applications

Efficient tools and algorithms for knowledge discovery in large data sets have been devised during the recent years. These methods exploit the capability of computers to search huge amounts of data in a fast and effective manner. However, the data to be analyzed is imprecise and afflicted with uncertainty. In the case of heterogeneous data sources such as text, audio and video, the data might moreover be ambiguous and partly conflicting. Besides, patterns and relationships of interest are usually vague and approximate. Thus, in order to make the information mining process more robust or say, human-like methods for searching and learning it requires tolerance towards imprecision, uncertainty and exceptions. Thus, they have approximate reasoning capabilities and are capable of handling partial truth. Properties of the aforementioned kind are typical soft computing. Soft computing techniques like Genetic

TSACO: Extending a context-aware recommendation system with Allen temporal operators

In this paper we present our research to extend a recommender system based on a semantic multicriteria ant colony algorithm to allow the use of Allen temporal operators. The system utilizes user’s learnt routes, including their associated context information, in order to predict the most likely route a user is following, given his current location and context data. The addition of temporal operators will increase the level of expressiveness of the queries the system can answer what will allow, in turn, more fine-tuned predictions. This more refined knowledge could then be used as the basis for offering services related to his current (or most likely future) context in the vicinity of the path the user is followingThis work has been supported by the Centre for the Development of Industrial Technology (CDTI) under the funding project CENIT-MIO! CENIT-2008 1019.Mocholí Agües, JA.; Jaén Martínez, FJ.; Krynicki, KK.; Catalá Bolós, A. (2012). TSACO: Extending a context-aware recommendation system with Allen temporal operators. En Ubiquitous Computing and Ambient Intelligence. Springer. 253-260. https://doi.org/10.1007/978-3-642-35377-2_35S253260Adomavicius, G., Tuzhilin, A.: Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions. IEEE Trans. Knowledge Data Eng. 17(6), 734–749 (2005)Picón, A., Rodríguez-Vaamonde, S., Jaén, J., Mocholi, J.A., García, D., Cadenas, A.: A statistical recommendation model of mobile services based on contextual evidences. Expert Systems with Applications 39(1), 647–653 (2012)Mocholi, J.A., Jaen, J., Krynicki, K., Catala, A., Picón, A., Cadenas, A.: Learning semantically-annotated routes for context-aware recommendations on map navigation systems. Applied Soft Computing 12(9), 3088–3098 (2012)Linn, Z.Z., Hla, K.H.S.: Temporal Database Queries for Recommender System using Temporal Logic. In: Intl. Symposium on Micro-NanoMechatronics and Human Science, pp. 1–6 (2006)Ullah, F., Sarwar, G., Lee, S.C., Park, Y.K., Moon, K.D., Kim, J.T.: Hybrid recommender system with temporal information. In: Intl. Conf. on Information Networking, pp. 421–425 (2012)Shakshuki, E., Trudel, A., Xu, Y., Li, B.: A Probabilistic Temporal Interval Algebra Based Multi-agent Scheduling System. In: International Joint Conference on Artificial Intelligence Workshop in Multi-Agent Information Retrieval and Recommender Systems, pp. 62–69 (2005)Allen, J.F.: Maintaining knowledge about temporal intervals. Commun. ACM 26(11), 832–843 (1983)Dorigo, M., Maniezzo, V., Colorni, A.: The Ant System: Optimization by a Colony of Cooperating Agents. IEEE Trans. Systems, Man and Cybernetics, Part B 26, 29–34 (1996)Dorigo, M., Stützle, T.: The ant colony optimization metaheuristic: Algorithms, applications and advances. In: Glover, F., Kochen-berger, G. (eds.) Handbook of Metaheuristics, pp. 251–285. Kluwer Academic Publishers (2003)Khan, L., McLeod, D.: Audio structuring and personalized retrieval using ontologies. IEEE Advances in Digital Libraries (2000)Liang, Y.C., Smith, A.E.: An Ant Colony Approach to the Orienteering Problem. Journal of the Chinese Institute of Industrial Engineers 23(5), 403–414 (2003