User Interactions with Multimedia Repositories using Natural Language Interfaces - OntoNL: an Architectural Framework and its Implementation

We present a generalized architectural framework for constructing and using natural language interfaces for interactions with multimedia repositories. The system allows the users to specify natural language queries about the multimedia content with rich semantics. It uses an extensive set of methodologies and tools for linguistic processing, and utilizes the MPEG-7 and the domain ontologies to reduce the ambiguities in the natural language and to rank the results. We describe the implementation of this framework for supporting interactions with a multimedia repository, described with the MPEG-7 MDS (Multimedia Description Schemes) structures, that also uses User Profile information for better ranking of the result queries. Categories and Subject Descriptors H.5.1 (Multimedia Information Systems) H.5.2 (User Interfaces):Natural Langauage

[1]  Chrisa Tsinaraki,et al.  An Ontology-Driven Framework for the Management of Semantic Metadata Describing Audiovisual Information , 2003, CAiSE.

[2]  Chrisa Tsinaraki,et al.  Integration of OWL Ontologies in MPEG-7 and TV-Anytime Compliant Semantic Indexing , 2004, CAiSE.

[3]  Ted Briscoe,et al.  Corpus Annotation for Parser Evaluation , 1999, ArXiv.

[4]  Enrico Motta,et al.  AQUA - Ontology-Based Question Answering System , 2004, MICAI.

[5]  Mark Lauer,et al.  Designing Statistical Language Learners: Experiments on Noun Compounds , 1996, ArXiv.

[6]  Fabio Crestani,et al.  Application of Spreading Activation Techniques in Information Retrieval , 1997, Artificial Intelligence Review.

[7]  Preslav Nakov,et al.  Scaling Up BioNLP : Application of a Text Annotation Architecture to Noun Compound Bracketing , 2005 .

[8]  R. Quirk,et al.  A university grammar of English , 1973 .

[9]  John R. Smith,et al.  MPEG-7 multimedia description schemes , 2001, IEEE Trans. Circuits Syst. Video Technol..

[10]  Frank Keller,et al.  Using the Web to Obtain Frequencies for Unseen Bigrams , 2003, CL.

[11]  Dan Klein,et al.  Feature-Rich Part-of-Speech Tagging with a Cyclic Dependency Network , 2003, NAACL.

[12]  George A. Miller,et al.  Introduction to WordNet: An On-line Lexical Database , 1990 .

[13]  Adwait Ratnaparkhi,et al.  A Maximum Entropy Model for Part-Of-Speech Tagging , 1996, EMNLP.

[14]  Nicola Guarino,et al.  OntoSeek: content-based access to the Web , 1999, IEEE Intell. Syst..

[15]  P. Resnik.  Selection and information: a class-based approach to lexical relationships , 1993 .

[16]  Amit P. Sheth,et al.  Managing Semantic Content for the Web , 2002, IEEE Internet Comput..

[17]  John A. Carroll,et al.  Applied morphological processing of English , 2001, Natural Language Engineering.

[18]  Stavros Christodoulakis,et al.  A Natural Language Model and a System for Managing TV-Anytime Information from Mobile Devices , 2004, NLDB.

[19]  Mitchell P. Marcus,et al.  A theory of syntactic recognition for natural language , 1979 .

[20]  Stavros Christodoulakis,et al.  A natural language model for managing TV-Anytime information in mobile environments , 2004, Personal and Ubiquitous Computing.