Music Retrieval and Recommendation Scheme Based on Varying Mood Sequences

A typical music clip consists of one or more segments with different moods and such mood information could be a crucial clue for determining the similarity between music clips. One representative mood has been selected for music clip for retrieval, recommendation or classification purposes, which often gives unsatisfactory result. In this paper, the authors propose a new music retrieval and recommendation scheme based on the mood sequence of music clips. The authors first divide each music clip into segments through beat structure analysis, then, apply the k-medoids clustering algorithm for grouping all the segments into clusters with similar features. By assigning a unique mood symbol for each cluster, one can transform each music clip into a musical mood sequence. For music retrieval, the authors use the Smith-Waterman (SW) algorithm to measure the similarity between mood sequences. However, for music recommendation, user preferences are retrieved from a recent music playlist or user interaction through the interface, which generates a music recommendation list based on the mood sequence similarity. The authors demonstrate that the proposed scheme achieves excellent performance in terms of retrieval accuracy and user satisfaction in music recommendation.

Integrating Interactive TV Services and the Web through Semantics

Interactive TV has started to penetrate broadcasting markets, providing a new user experience through novel services to subscribers and new revenue opportunities for companies. Personalization and intelligent behavior, such as proactive content delivery are considered key features for the services of the future TV. However, most of the work in this area is limited to personalization of electronic program guides and advanced program recommendation. In this article, the authors adopt a more horizontal approach and describe the application of concepts, practices and modern Web trends to the TV domain in the context of the POLYSEMA platform. A key characteristic of this approach is the formal modeling of multimedia and user semantics that enables novel TV services. Specifically, Semantic Web methodologies are employed (e.g., ontologies and rules) while compatibility with the MPEG-7 standard is also pursued. The paper describes the overall architecture of the platform, provides implementation details and investigates business issues.

Semantic Search on Unstructured Data

Studies agree that searchers are often not satisfied with the performance of current enterprise search engines. As a consequence, more scientists worldwide are actively investigating new avenues for searching to improve retrieval performance. This paper contributes to YASA (Your Adaptive Search Agent), a fully implemented and thoroughly evaluated ontology-based information retrieval system for the enterprise. A salient particularity of YASA is that large parts of the ontology are automatically filled with facts by recycling and transforming existing data. YASA offers context-based personalization, faceted navigation, as well as semantic search capabilities. YASA has been deployed and evaluated in the pharmaceutical research department of Roche, Penzberg, and results show that already semantically simple ontologies suffice to considerably improve search performance.

Ontology-Enhanced User Interfaces

Ontologies have been increasingly used in software systems in the past years. However, in many of those systems, the ontologies are hidden “under the hood”. While a lot of useful applications of ontologies on the database and business logic layer have been proposed, the employment of ontologies in user interfaces has been gaining comparatively little attention so far. For providing a deeper understanding of that field as well as assisting developers of ontology-enhanced user interfaces, the authors give an overview of such applications and introduce a schema for characterizing the requirements of ontology-enhanced user interfaces. With this article, a state of the art survey of approaches is presented along with promising research directions.

A Pattern-Based Method for Re-Engineering Non-Ontological Resources into Ontologies

To speed up the ontology development process, ontology developers are reusing all available ontological and non-ontological resources, such as classification schemes, thesauri, lexicons, and so forth, that have already reached some consensus. Non-ontological resources are highly heterogeneous in their data model and storage system (or implementation). The reuse of these non-ontological resources involves their re-engineering into ontologies. This paper presents a method for re-engineering non-ontological resources into ontologies. The method is based on so-called re-engineering patterns, which define a procedure that transforms the non-ontological resource components into ontology representational primitives using WordNet for making explicit the relations among the non-ontological resource terms. The paper also provides the description of NOR2O, a software library that implements the transformations suggested by the patterns. Finally, it depicts an evaluation of the method, patterns, and software library proposed.

A Tool Suite to Enable Web Designers, Web Application Developers and End-users to Handle Semantic Data

Current web application development requires highly qualified staff, dealing with an extensive number of architectures and technologies. When these applications incorporate semantic data, the list of skill requirements becomes even larger, leading to a high adoption barrier for the development of semantically enabled Web applications. This paper describes VPOET, a tool focused mainly on two types of users: web designers and web application developers. By using this tool, web designers do not need specific skills in semantic web technologies to create web templates to handle semantic data. Web application developers incorporate those templates into their web applications, by means of a simple mechanism based in HTTP messages. End-users can use these templates through a Google Gadget. As web designers play a key role in the system, an experimental evaluation has been conducted, showing that VPOET provides good usability features for a representative group of web designers in a wide range of competencies in client-side technologies, ranging from amateur HTML developers to professional web designers.

Enhancing Folksonomy-Based Content Retrieval with Semantic Web Technology

While Flickr, a widely-known photo sharing system, allows users to describe their own photos with tags (aka. folksonomy tags) for indexing purposes, its tag-based photo retrieval function is severely hampered by the inherent nature of folksonomy tags. This paper presents SemFlickr, an application which enhances the search in Flickr with its semantic query suggestion feature. SemFlickr employs SQORE, an ontology retrieval system, to retrieve relevant ontologies from the Semantic Web and then derives query term suggestions from those ontologies. To ensure that the highly related photos will appear at the top of the results, SemFlickr takes the ontological relations among the given query terms to assign tag scores and then generates its ranked results. Experimental outcomes are encouraging and reveal a number of useful insights for developing applications that integrate the Semantic Web and Web 2.0 together.

Adaptive Hybrid Semantic Selection of SAWSDL Services with SAWSDL-MX2

In this paper, the authors present an adaptive, hybrid semantic matchmaker for SAWSDL services, called SAWSDL-MX2. It determines three types of semantic matching of an advertised service with a requested one, which are described in standard SAWSDL: logic-based, text-similarity-based and XML-tree edit-based structural similarity. Before selection, SAWSDL-MX2 learns the optimal aggregation of these different matching degrees off-line over a random subset of a given SAWSDL service retrieval test collection by exploiting a binary support vector machine-based classifier with ranking. The authors present a comparative evaluation of the retrieval performance of SAWSDL-MX2.

Building Chemical Ontology for Semantic Web Using Substructures Created by Chem-BLAST

Efficient and user friendly ontologies are crucial for the effective use of chemical structural data on compounds. This paper describes an automated technique to create a structural ontology for compounds like ligands, co-factors and inhibitors of protein and DNA molecules using a technique developed from Perl scripts, which use a relational database for input and output, called Chem-BLAST (Chemical Block Layered Alignment of Substructure Technique). This technique recursively identifies substructures using rules that operate on the atomic connectivity of compounds. Substructures obtained from the compounds are compared to generate a data model expressed as triples. A chemical ontology of the substructures is made up of numerous interconnected ‘hubs-and-spokes’ is generated in the form of a data tree. This data-tree is used in a Web interface to allow users to zoom into compounds of interest by stepping through the hubs from the top to the bottom of the data-tree. The technique has been applied for (a) 2-D and 3-D structural data for AIDS1; (b) ~60,000 structures from the PDB 2,3. Recently, this technique has been applied to approximately 3,000,000 compounds from PubChem4,5,6. Plausible ways to use this data model for the Semantic Web are also discussed.

An Ontology-Based, Cross-Application Context Modeling and Management Service

Context awareness is a key issue for applications within heterogeneous and networked environments. In terms of efficiency and reusability, such applications need to be separated from the problems of context gathering and modeling, but should instead profit from and contribute to cross-application context information. For this purpose, an ontology-based, cross-application context modeling and management service is required to provide appropriate support for the variety of conceivable application scenarios. Although there have been numerous approaches dealing with application-independent context management, none of them sufficiently supports the vision of cross-application context handling. Therefore, this paper presents CroCo, an ontology-based context management service that allows for cross-application context gathering, modeling, and provision. The authors successfully verified and tested the application independency and practicability of this novel concept within three different projects with disparate application scenarios.