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Video Data Mining: Rhythms in a Movie

by Kimiaki Shirahama, Kazuhisa Iwamoto, Kuniaki Uehera - Procs. IEEE Int. Conf. Multimedia and Expo, ICME , 2004
"... The task to discover useful editing patterns from a pro-fessional video, such as a movie, is one of the main purpose of video data mining. These patterns successfully convey editor’s intentions to the viewers. But, data mining on mul-timedia data like a movie is a challenging task, due to the compli ..."
Abstract - Cited by 2 (0 self) - Add to MetaCart
The task to discover useful editing patterns from a pro-fessional video, such as a movie, is one of the main purpose of video data mining. These patterns successfully convey editor’s intentions to the viewers. But, data mining on mul-timedia data like a movie is a challenging task, due

Video Data Mining with Learning Cellular Automata

by Behnaz Meshkboo, Mohammadreza Kangavari
"... Data mining has been the focus of many analysts who was interested to knowledge extraction in data. The new concept called video data mining has arisen for efficient video data management which requires identifying semantic patterns for finding semantic relationships between events occurring in a mo ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
Data mining has been the focus of many analysts who was interested to knowledge extraction in data. The new concept called video data mining has arisen for efficient video data management which requires identifying semantic patterns for finding semantic relationships between events occurring in a

Mining sequential patterns from temporal streaming data

by A. Marascu, F. Masseglia - in ‘Proceedings of the first ECML/PKDD Workshop on Mining Spatio-Temporal Data (MSTD’05), held in conjunction with the 9th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD’05 , 2005
"... Abstract. In recent years, emerging applications introduced new constraints for data mining methods. These constraints are typical of a new kind of data: the data streams. In a data stream processing, memory usage is restricted, new elements are generated continuously and have to be considered as fa ..."
Abstract - Cited by 6 (0 self) - Add to MetaCart
pattern mining. In this paper, we propose an algorithm based on sequences alignment for mining approximate sequential patterns in Web usage data streams. To meet the constraint of one scan, a greedy clustering algorithm associated to an alignment method are proposed. We will show that our proposal is able

Video Data Mining: Semantic Indexing and Event Detection from the Association Perspective

by Xingquan Zhu, Xindong Wu, Ahmed K. Elmagarmid, Zhe Feng, Lide Wu - IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING , 2005
"... Advances in the media and entertainment industries, including streaming audio and digital TV, present new challenges for managing and accessing large audio-visual collections. Current content management systems support retrieval using low-level features, such as motion, color, and texture. However, ..."
Abstract - Cited by 30 (1 self) - Add to MetaCart
knowledge-based video indexing and content management framework for domain specific videos (using basketball video as an example). We will provide a solution to explore video knowledge by mining associations from video data. The explicit definitions and evaluation measures (e.g., temporal support

Mining sequences of temporal intervals

by Steffen Kempe - In 10th Europ. Conf. on Principles and Practice of Knowledge Discovery in Databases , 2006
"... Abstract. Recently a new type of data source came into the focus of knowledge discovery from temporal data: interval sequences. In contrast to event sequences, interval sequences contain labeled events with a tem-poral extension. However, existing algorithms for mining patterns from interval sequenc ..."
Abstract - Cited by 2 (2 self) - Add to MetaCart
Abstract. Recently a new type of data source came into the focus of knowledge discovery from temporal data: interval sequences. In contrast to event sequences, interval sequences contain labeled events with a tem-poral extension. However, existing algorithms for mining patterns from interval

TEMPORAL SEQUENTIAL PATTERN Abstract IN DATA MINING TASKS

by Dr. Naveeta Mehta
"... The rapid increase in the data available leads to the difficulty for analyzing those data and different types of frameworks are required for unearthing useful knowledge that can be extracted from such databases. The field of temporal data mining is relatively young and one expects to see many new de ..."
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The rapid increase in the data available leads to the difficulty for analyzing those data and different types of frameworks are required for unearthing useful knowledge that can be extracted from such databases. The field of temporal data mining is relatively young and one expects to see many new

Pattern mining in visual concept streams

by Lexing Xie - Proc. IEEE Intl. Conf. Multimedia and Expo , 2006
"... Pattern mining algorithms are often much easier applied than quantitatively assessed. In this paper we address the pattern evaluation problem by looking at both the capability of models and the difficulty of target concepts. We use four different data mining models: frequent itemset mining, k-means ..."
Abstract - Cited by 11 (3 self) - Add to MetaCart
-means clustering, hidden Markov model, and hierarchical hidden Markov model to mine 39 concept streams from the a 137-video broadcast news collection from TRECVID-2005. We hypothesize that the discovered patterns can reveal semantics beyond the input space, and thus evaluate the patterns against a much larger

Temporal granular logic for temporal data mining

by Paul Cotofrei, Kilian Stoffel
"... Abstract — In this article, a formalism for a specific temporal data mining task (the discovery of rules, inferred from databases of events having a temporal dimension), is defined. The proposed theoretical framework, based on first-order temporal logic, allows the definition of the main notions (ev ..."
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Abstract — In this article, a formalism for a specific temporal data mining task (the discovery of rules, inferred from databases of events having a temporal dimension), is defined. The proposed theoretical framework, based on first-order temporal logic, allows the definition of the main notions

A sparsity constraint for topic models application to temporal activity mining,” NIPS

by Jagannadan Varadarajan, Rémi Emonet, Jean-marc Odobez , 2010
"... We address the mining of sequential activity patterns from document logs given as word-time occurrences. We achieve this using topics that model both the cooccurrence and the temporal order in which words occur within a temporal window. Discovering such topics, which is particularly hard when multip ..."
Abstract - Cited by 4 (1 self) - Add to MetaCart
We address the mining of sequential activity patterns from document logs given as word-time occurrences. We achieve this using topics that model both the cooccurrence and the temporal order in which words occur within a temporal window. Discovering such topics, which is particularly hard when

Motion Mining

by Stan Sclaroff, George Kollios, Margrit Betke, Romer Rosales - In Proceedings of the 2 nd Int’l Workshop on Multimedia Databases and Image Communication, MDIC’01 , 2001
"... Abstract. A long-term research effort to support data mining applications for video databases of human motion is described. Due to the spatio-temporal nature of human motion data, novel methods for indexing and mining databases of time series data of human motion are required. Further, since data mi ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
mining requires a significant sample size to accurately model patterns in the data, algorithms that automatically extract motion trajectories and time series data from video are required. A preliminary system for estimating human motion in video, as well as indexing and data mining of the resulting
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