Automated speech and audio analysis for semantic access to multimedia

The deployment and integration of audio processing tools can enhance the semantic annotation of multimedia content, and as a consequence, improve the effectiveness of conceptual access tools. This paper overviews the various ways in which automatic speech and audio analysis can contribute to increased granularity of automatically extracted metadata. A number of techniques will be presented, including the alignment of speech and text resources, large vocabulary speech recognition, key word spotting and speaker classification. The applicability of techniques will be discussed from a media crossing perspective. The added value of the techniques and their potential contribution to the content value chain will be illustrated by the description of two (complementary) demonstrators for browsing broadcast news archives

Formally analysing the concepts of domestic violence.

The types of police inquiries performed these days are incredibly diverse. Often data processing architectures are not suited to cope with this diversity since most of the case data is still stored as unstructured text. In this paper Formal Concept Analysis (FCA) is showcased for its exploratory data analysis capabilities in discovering domestic violence intelligence from a dataset of unstructured police reports filed with the regional police Amsterdam-Amstelland in the Netherlands. From this data analysis it is shown that FCA can be a powerful instrument to operationally improve policing practice. For one, it is shown that the definition of domestic violence employed by the police is not always as clear as it should be, making it hard to use it effectively for classification purposes. In addition, this paper presents newly discovered knowledge for automatically classifying certain cases as either domestic or non-domestic violence is. Moreover, it provides practical advice for detecting incorrect classifications performed by police officers. A final aspect to be discussed is the problems encountered because of the sometimes unstructured way of working of police officers. The added value of this paper resides in both using FCA for exploratory data analysis, as well as with the application of FCA for the detection of domestic violence.Formal concept analysis (FCA); Domestic violence; Knowledge discovery in databases; Text mining; Exploratory data analysis; Knowledge enrichment; Concept discovery;

Semantic browsing of digital collections

Visiting museums is an increasingly popular pastime. Studies have shown that visitors can draw on their museum experience, long after their visit, to learn new things in practical situations. Rather than viewing a visit as a single learning event, we are interested in ways of extending the experience to allow visitors to access online resources tailored to their interests. Museums typically have extensive archives that can be made available online, the challenge is to match these resources to the visitor’s interests and present them in a manner that facilitates exploration and engages the visitor. We propose the use of knowledge level resource descriptions to identify relevant resources and create structured presentations. A system that embodies this approach, which is in use in a UK museum, is presented and the applicability of the approach to the broader semantic web is discussed

Document management and retrieval for specialised domains : an evolutionary user-based approach

Browsing marked-up documents by traversing hyperlinks has become probably the most important means by which documents are accessed, both via the World Wide Web (WWW) and organisational Intranets. However, there is a pressing demand for document management and retrieval systems to deal appropriately with the massive number of documents available. There are two classes of solution: general search engines, whether for the WWW or an Intranet, which make little use of specific domain knowledge or hand-crafted specialised systems which are costly to build and maintain. The aim of this thesis was to develop a document management and retrieval system suitable for small communities as well as individuals in specialised domains on the Web. The aim was to allow users to easily create and maintain their own organisation of documents while ensuring continual improvement in the retrieval performance of the system as it evolves. The system developed is based on the free annotation of documents by users and is browsed using the concept lattice of Formal Concept Analysis (FCA). A number of annotation support tools were developed to aid the annotation process so that a suitable system evolved. Experiments were conducted in using the system to assist in finding staff and student home pages at the School of Computer Science and Engineering, University of New South Wales. Results indicated that the annotation tools provided a good level of assistance so that documents were easily organised and a lattice-based browsing structure that evolves in an ad hoc fashion provided good efficiency in retrieval performance. An interesting result suggested that although an established external taxonomy can be useful in proposing annotation terms, users appear to be very selective in their use of terms proposed. Results also supported the hypothesis that the concept lattice of FCA helped take users beyond a narrow search to find other useful documents. In general, lattice-based browsing was considered as a more helpful method than Boolean queries or hierarchical browsing for searching a specialised domain. We conclude that the concept lattice of Formal Concept Analysis, supported by annotation techniques is a useful way of supporting the flexible open management of documents required by individuals, small communities and in specialised domains. It seems likely that this approach can be readily integrated with other developments such as further improvements in search engines and the use of semantically marked-up documents, and provide a unique advantage in supporting autonomous management of documents by individuals and groups - in a way that is closely aligned with the autonomy of the WWW

Detecting domestic violence.

Over 90% of the case data from police inquiries is stored as unstructured text in police databases. We use the combination of Formal Concept Analysis and Emergent Self Organizing Maps for exploring a dataset of unstructured police reports out of the Amsterdam-Amstelland police region in the Netherlands. In this paper, we specifically aim at making the reader familiar with how we used these two tools for browsing the dataset and how we discovered useful patterns for labelling cases as domestic or as non-domestic violence.Formal concept analysis (FCA); Emergent SOM; Domestic violence; Knowledge discovery in databases; Text mining; Exploratory data analysis;