Natural language query processing in ontology based multimedia databases

Aygül, Filiz Alaca
In this thesis a natural language query interface is developed for semantic and spatio-temporal querying of MPEG-7 based domain ontologies. The underlying ontology is created by attaching domain ontologies to the core Rhizomik MPEG-7 ontology. The user can pose concept, complex concept (objects connected with an “AND” or “OR” connector), spatial (left, right . . . ), temporal (before, after, at least 10 minutes before, 5 minutes after . . . ), object trajectory and directional trajectory (east, west, southeast . . . , left, right, upwards . . . ) queries to the system. Furthermore, the system handles the negative meaning in the user input. When the user enters a natural language (NL) input, it is parsed with the link parser. According to query type, the objects, attributes, spatial relation, temporal relation, trajectory relation, time filter and time information are extracted from the parser output by using predefined rules. After the information extraction, SPARQL queries are generated, and executed against the ontology by using an RDF API. Results are retrieved and they are used to calculate spatial, temporal, and trajectory relations between objects. The results satisfying the required relations are displayed in a tabular format and user can navigate through the multimedia content.


Ontology-based spatio-temporal video management system
Şimşek, Atakan; Çiçekli, Fehime Nihan; Department of Computer Engineering (2009)
In this thesis, a system, called Ontology-Based Spatio-Temporal Video Management System (OntoVMS) is developed in order to supply a framework which can be used for semantic data modeling and querying in video files. OntoVMS supports semantic data modeling which can be divided into concept modeling, spatio-temporal relation and trajectory data modeling. The system uses Rhizomik MPEG-7 Ontology as the core ontology. Moreover ontology expression capability is extended by automatically attaching domain ontologi...
Improvement of corpus-based semantic word similarity using vector space model
Esin, Yunus Emre; Alpaslan, Ferda Nur; Department of Computer Engineering (2009)
This study presents a new approach for finding semantically similar words from corpora using window based context methods. Previous studies mainly concentrate on either finding new combination of distance-weight measurement methods or proposing new context methods. The main di fference of this new approach is that this study reprocesses the outputs of the existing methods to update the representation of related word vectors used for measuring semantic distance between words, to improve the results further. ...
Using semantic web services for data integration in banking domain
Okat, Çağlar; Doğru, Ali Hikmet; Department of Computer Engineering (2010)
A semantic model oriented transformation mechanism is developed for the centralization of intra-enterprise data integration. Such a mechanism is especially crucial in the banking domain which is selected in this study. A new domain ontology is constructed to provide basis for annotations. A bottom-up approach is preferred for semantic annotations to utilize existing web service definitions. Transformations between syntactic web service XML responses and semantic model concepts are defined in transformation ...
Automatic composition of semantic web services with the abductive event calculus
Kırcı, Esra; Çiçekli, Fehime Nihan; Department of Computer Engineering (2008)
In today's world, composite web services are widely used in service oriented computing, web mashups and B2B Applications etc. Most of these services are composed manually. However, the complexity of manually composing web services increase exponentially with the increase in the number of available web services, the need for dynamically created/updated/discovered services and the necessity for higher amount of data bindings and type mappings in longer compositions. Therefore, current highly manual web servic...
Ontology learning and question answering (qa) systems
Başkurt, Meltem; Alpaslan, Ferda Nur; Department of Computer Engineering (2010)
Ontology Learning requires a deep specialization on Semantic Web, Knowledge Representation, Search Engines, Inductive Learning, Natural Language Processing, Information Storage, Extraction and Retrieval. Huge amount of domain specific, unstructured on-line data needs to be expressed in machine understandable and semantically searchable format. Currently users are often forced to search manually in the results returned by the keyword-based search services. They also want to use their native languages to expr...
Citation Formats
F. A. Aygül, “Natural language query processing in ontology based multimedia databases,” M.S. - Master of Science, Middle East Technical University, 2010.