9,621 research outputs found
Using association rule mining to enrich semantic concepts for video retrieval
In order to achieve true content-based information retrieval on video we should analyse and index video with
high-level semantic concepts in addition to using user-generated tags and structured metadata like title, date,
etc. However the range of such high-level semantic concepts, detected either manually or automatically,
usually limited compared to the richness of information content in video and the potential vocabulary of
available concepts for indexing. Even though there is work to improve the performance of individual concept
classiïŹers, we should strive to make the best use of whatever partial sets of semantic concept occurrences
are available to us. We describe in this paper our method for using association rule mining to automatically
enrich the representation of video content through a set of semantic concepts based on concept co-occurrence
patterns. We describe our experiments on the TRECVid 2005 video corpus annotated with the 449 concepts
of the LSCOM ontology. The evaluation of our results shows the usefulness of our approach
Visual Information Retrieval in Endoscopic Video Archives
In endoscopic procedures, surgeons work with live video streams from the
inside of their subjects. A main source for documentation of procedures are
still frames from the video, identified and taken during the surgery. However,
with growing demands and technical means, the streams are saved to storage
servers and the surgeons need to retrieve parts of the videos on demand. In
this submission we present a demo application allowing for video retrieval
based on visual features and late fusion, which allows surgeons to re-find
shots taken during the procedure.Comment: Paper accepted at the IEEE/ACM 13th International Workshop on
Content-Based Multimedia Indexing (CBMI) in Prague (Czech Republic) between
10 and 12 June 201
Digital Image Access & Retrieval
The 33th Annual Clinic on Library Applications of Data Processing, held at the University of Illinois at Urbana-Champaign in March of 1996, addressed the theme of "Digital Image Access & Retrieval." The papers from this conference cover a wide range of topics concerning digital imaging technology for visual resource collections. Papers covered three general areas: (1) systems, planning, and implementation; (2) automatic and semi-automatic indexing; and (3) preservation with the bulk of the conference focusing on indexing and retrieval.published or submitted for publicatio
ELICA: An Automated Tool for Dynamic Extraction of Requirements Relevant Information
Requirements elicitation requires extensive knowledge and deep understanding
of the problem domain where the final system will be situated. However, in many
software development projects, analysts are required to elicit the requirements
from an unfamiliar domain, which often causes communication barriers between
analysts and stakeholders. In this paper, we propose a requirements ELICitation
Aid tool (ELICA) to help analysts better understand the target application
domain by dynamic extraction and labeling of requirements-relevant knowledge.
To extract the relevant terms, we leverage the flexibility and power of
Weighted Finite State Transducers (WFSTs) in dynamic modeling of natural
language processing tasks. In addition to the information conveyed through
text, ELICA captures and processes non-linguistic information about the
intention of speakers such as their confidence level, analytical tone, and
emotions. The extracted information is made available to the analysts as a set
of labeled snippets with highlighted relevant terms which can also be exported
as an artifact of the Requirements Engineering (RE) process. The application
and usefulness of ELICA are demonstrated through a case study. This study shows
how pre-existing relevant information about the application domain and the
information captured during an elicitation meeting, such as the conversation
and stakeholders' intentions, can be captured and used to support analysts
achieving their tasks.Comment: 2018 IEEE 26th International Requirements Engineering Conference
Workshop
The FĂschlĂĄr-News-Stories system: personalised access to an archive of TV news
The âFĂschlĂĄrâ systems are a family of tools for capturing, analysis, indexing, browsing, searching and summarisation of digital video information. FĂschlĂĄr-News-Stories, described in this paper, is one of those systems, and provides access to a growing archive of broadcast TV news. FĂschlĂĄr-News-Stories has several notable features including the fact that it automatically records TV news and segments a broadcast news program into stories, eliminating advertisements and credits at the start/end of the broadcast. FĂschlĂĄr-News-Stories supports access to individual stories via calendar lookup, text search through closed captions, automatically-generated links between related stories, and personalised access using a personalisation and recommender system based on collaborative filtering. Access to individual news stories is supported either by browsing keyframes with synchronised closed captions, or by playback of the recorded video. One strength of the FĂschlĂĄr-News-Stories system is that it is actually used, in practice, daily, to access news. Several aspects of the FĂschlĂĄr systems have been published before, bit in this paper we give a summary of the FĂschlĂĄr-News-Stories system in operation by following a scenario in which it is used and also outlining how the underlying system realises the functions it offers
Applying semantic web technologies to knowledge sharing in aerospace engineering
This paper details an integrated methodology to optimise Knowledge reuse and sharing, illustrated with a use case in the aeronautics domain. It uses Ontologies as a central modelling strategy for the Capture of Knowledge from legacy docu-ments via automated means, or directly in systems interfacing with Knowledge workers, via user-defined, web-based forms. The domain ontologies used for Knowledge Capture also guide the retrieval of the Knowledge extracted from the data using a Semantic Search System that provides support for multiple modalities during search. This approach has been applied and evaluated successfully within the aerospace domain, and is currently being extended for use in other domains on an increasingly large scale
Memory Rehabilitation Strategies in Nonsurgical Temporal Lobe Epilepsy: A Review
open8siPeople with temporal lobe epilepsy (TLE) who have not undergone epilepsy surgery often complain of memory deficits. Cognitive re-
habilitation is employed as a remedial intervention in clinical settings, but research is limited and findings concerning efficacy and the criteria
for choosing different approaches have been inconsistent. We aimed to appraise existing evidence on memory rehabilitation in nonsurgical
individuals with temporal lobe epilepsy and to ascertain the effectiveness of specific strategies. A scoping review was preferred given the het-
erogeneous nature of the interventions. A comprehensive literature search using MEDLINE, EMBASE, CINAHL, AMED, Scholars Portal/
PSYCHinfo, Proceedings First, and ProQuest Dissertations and Theses identified articles published in English before February 2016. The
search retrieved 372 abstracts. Of 25 eligible studies, six were included in the final review. None included pediatric populations. Strategies
included cognitive training, external memory aids, brain training, and noninvasive brain stimulation. Selection criteria tended to be general.
Overall, there was insufficient evidence to make definitive conclusions regarding the efficacy of traditional memory rehabilitation strategies,
brain training, and noninvasive brain stimulation. The review suggests that cognitive rehabilitation in nonsurgical TLE is underresearched and
that there is a need for a systematic evaluation in this population.embargoed_20180216DEL FELICE, Alessandra; Alderighi, Marzia; Martinato, Matteo; Grisafi, Davide; Bosco, Anna; Thompson, Pamela J.; Sander, Josemir W.; Masiero, StefanoDEL FELICE, Alessandra; Alderighi, Marzia; Martinato, Matteo; Grisafi, Davide; Bosco, Anna; Thompson, Pamela J.; Sander, Josemir W.; Masiero, Stefan
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