Topic
Multimedia database
About: Multimedia database is a research topic. Over the lifetime, 1404 publications have been published within this topic receiving 19856 citations. The topic is also known as: Multimedia database & MMDB.
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18 Sep 2000
TL;DR: The algorithm tries to make the benefits of collaborative filtering available to application domains where collaborative filtering could not yet be applied due to lack of the critical mass of users or improper content structure.
Abstract: Presents an information filtering and adaptive personalisation algorithm for arbitrary information systems based on databases. This algorithm is called GRAS (Gaussian Rating Adaptation Scheme), and it combines content-based and collaborative filtering. The goal is to filter the retrieved documents of a query according to the personal interests of a user and to sort them according to their personal relevance. The algorithm tries to make the benefits of collaborative filtering available to application domains where collaborative filtering could not yet be applied due to lack of the critical mass of users or improper content structure. The algorithm collects background information about the user and the content by implicit and explicit feedback techniques. This information is then used to consecutively adapt user and object profiles according their maturity. The described algorithm is applicable to the personalisation of any kind of application domain, even on multimedia data. GRAS is implemented in the multimedia database MultiMAP as a generic personalisation provider module.
14 citations
DOI•
01 Jan 1994
TL;DR: This work follows the SGML/HyTime international standard by designing a document type declaration (DTD) for multimedia news articles and builds an object oriented model of multimedia news documents based on this DTD.
Abstract: We describe the design of a multimedia database for a distributed news-on-demand multimedia information system. News–on–demand is an application that utilizes broadband network services to deliver news articles to subscribers in the form of multimedia documents. Different news providers insert articles into the database, which is then accessed by remote users over a broadband network. Multimedia documents are composite objects where the component objects have spatial and temporal relationships which need to be captured in the database. Modeling of multimedia documents involves three issues: (1) modeling of individual document components (i.e., monomedia objects such as text, images, etc), (2) modeling of the document structure, and (3) modeling of the presentation structure. We take an object-oriented approach to dealing with these issues. Within (1), our research has so far concentrated on text. We use an annotation based scheme where entire text is stored as a single document and the formatting markups are represented as annotations on the text. To model the structure of multimedia news documents , we follow the SGML/HyTime international standard by designing a document type declaration (DTD) for multimedia news articles. We build an object oriented model of multimedia news documents based on this DTD. Finally , we model the presentational aspects (e.g., fonts, number of columns, playing of audio and video) as objects and store them in the database..
13 citations
20 Apr 2020
TL;DR: Comprehensive experiments show that the proposed methods with learned index structure perform much better than the state-of-the-art external memory-based ANNS methods in terms of I/O efficiency and accuracy.
Abstract: Approximate nearest neighbour search (ANNS) in high dimensional space is a fundamental problem in many applications, such as multimedia database, computer vision and information retrieval. Among many solutions, data-sensitive hashing-based methods are effective to this problem, yet few of them are designed for external storage scenarios and hence do not optimized for I/O efficiency during the query processing. In this paper, we introduce a novel data-sensitive indexing and query processing framework for ANNS with an emphasis on optimizing the I/O efficiency, especially, the sequential I/Os. The proposed index consists of several lists of point IDs, ordered by values that are obtained by learned hashing (i.e., mapping) functions on each corresponding data point. The functions are learned from the data and approximately preserve the order in the high-dimensional space. We consider two instantiations of the functions (linear and non-linear), both learned from the data with novel objective functions. We also develop an I/O efficient ANNS framework based on the index. Comprehensive experiments on six benchmark datasets show that our proposed methods with learned index structure perform much better than the state-of-the-art external memory-based ANNS methods in terms of I/O efficiency and accuracy.
13 citations
26 Sep 2001
TL;DR: The Region Frequency and Inverse Picture Frequency (RF/sup */IPF) weighting, a measure developed to unify region-based multimedia retrieval systems with text-based information retrieval systems, is presented.
Abstract: The region-based approach has become a popular research trend in the field of multimedia database retrieval. We present the Region Frequency and Inverse Picture Frequency (RF/sup */IPF) weighting, a measure developed to unify region-based multimedia retrieval systems with text-based information retrieval systems. The weighting measure gives the highest weight to regions that occur often in a small number of images in the database. These regions are considered discriminators. With this weighting measure, we can blend image retrieval techniques with TF/sup */IDF-based text retrieval techniques for large-scale Web applications. The RF/sup */IPF weighting has been implemented as a part of our experimental SIMPLIcity image retrieval system and tested on a database of about 200000 general-purpose images. Experiments have shown that this technique is effective in discriminating images of different semantics. Additionally, the overall similarity approach enables a simple querying interface for multimedia information retrieval systems.
13 citations
TL;DR: A usable interface to collect and organise respiratory-related data in a single multimedia database, named LungSounds@UA, composed by a multilayer of windows, was developed and some drawbacks were identified.
Abstract: The development of graphical user interfaces GUIs has been an emergent demand in the area of healthcare technologies. Specifically for respiratory healthcare there is a lack of tools to produce a complete multimedia database, where respiratory sounds and other clinical data are available in a single repository. This is essential for a complete patients' assessment and management in research/clinical settings. Therefore, this study aimed to develop a usable interface to collect and organise respiratory-related data in a single multimedia database. A GUI, named LungSounds@UA, composed by a multilayer of windows, was developed. The usability of the user-centred interface was assessed in a pilot study and in an evaluation session. The users testified the utility of the application and its great potential for research/clinical settings. However, some drawbacks were identified, such as a certain difficulty to intuitively navigate in the great amount of the available information, which will inform future developments.
13 citations