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This paper proposes a novel semantic content analysis framework for reliable video event extraction which is essential for high-level video indexing and retrieval. In this work, we target to address the unique challenges posed in rare event detection, where positive examples (i.e., eventful data points) are vastly outnumbered and thus overshadowed by negative ones (i.e., noneventful data points)....
We use a Markovian model to capture the habitual user profiles of an information access system. In this model, the general as well as the individual for each user, profile is captured in the form of a Markovian process where the states are the keywords asked to the system by the users and a transition from state to state corresponds to the order theses keywords appeared in the queries. Under this...
Extraction of quantitative information about spatio- temporal events happening in cells is the key to understanding biological processes. In this paper we present a finite state machine (FSM)-based model for specification and identification of spatio-temporal events at the single-cell level. Cells are modeled as objects with specific attributes such as color, size, shape, etc., and events are modeled...
The proliferation of digital libraries and the large amount of existing documents raise important issues in efficient handling of documents. Printed texts in documents need to be converted into digital format and semantic information need to be parsed and managed for effective retrieval. In this work, we attempt to solve the problems faced by current web based archives, where large scale repositories...
The integration of knowledge from heterogeneous information sources and applications does not only require the conceptual mapping of information structures, but it also requires the treatment of semantic meta knowledge (i.e. knowledge about knowledge) in a generic manner. We describe a generic mechanism for (i) modeling and (ii) querying semantic meta knowledge in the context of RDF repositories....
In this paper, a supervised multi-class classification approach called Adaptive Selection of Information Components (ASIC) is presented. ASIC has the facilities to (i) handle both numerical and nominal features in a data set, (ii) pre-process the training data set to accentuate the spatial differences among the classes in the training data set to reduce further computational load requirements, and...
This paper proposes a system to facilitate exchange of information by automatically finding experts, competent in answering a given question. Our objective is to provide an online tool, which enables individuals within a potentially large organization to search for experts in a certain area, which may not be represented in company organization or reporting lines. The advantage of the proposed system...
Bacterial colony enumeration has applications in many different assays such as antibiotic screening, toxicology testing, and genotoxicity measuring. The counting of bacterial colony is usually performed by well-trained technicians manually. However, this manual enumeration process has a very low throughput, and is time consuming and labor intensive in practice. To provide consistent and accurate results...
Recognizing textual entailment (TE) is a complex task involving knowledge from many different sources. One major source of information in this task is event factuality, since the inferences derivable from factual eventualities are different from those judged as possible or as non-existent. Some TE systems already factor in factuality features at the local level, but determining the factuality of events...
The OntoNotes project is creating a corpus of large-scale, accurate, and integrated annotation of multiple levels of the shallow semantic structure in text. Such rich, integrated annotation covering many levels will allow for richer, cross-level models enabling significantly better automatic semantic analysis. At the same time, it demands a robust, efficient, scalable mechanism for storing and accessing...
This paper presents a robust classification of dialog acts from text utterances. Two different types, namely, bag-of-words and syntactic relationship among words, were used to extract the discourse level features from the transcript of utterances. Subsequently a number of feature mining methods have been used to identify the most relevant features and their roles in classifying dialog acts. The selected...
Many recent advances in complex domains such as natural language processing (NLP) have taken a discriminative approach in conjunction with the global application of structural and domain specific constraints. We introduce LBJ, a new modeling language for specifying exact inference systems of this type, combining ideas from machine learning, optimization, first order logic (FOL), and object oriented...
The Web was projected to support resource sharing at global level. Nowadays, this resource sharing is very limited, mainly respect to imperfect information retrieval and hidden Web. The semantic Web comes up as a possible solution to such limitations. The virtual communities of practice are groups of people who get in with each other virtually and share their knowledge. The use of semantic Web technologies...
Recently, remote sensing images increase greatly in the repositories. To achieve efficient storage and indexing, we introduce a JPEG2000 compression frame which puts emphasis on selection and designation of regions of interest (ROI). Firstly, SIFT is applied for feature extraction, descriptor generation and point matching to locate ROI. Secondly, an approach is proposed for computing transformation...
This paper discusses a method of studying the region style classification of Chinese folk songs with support vector machine (SVM). According to geographical region of China, We have classified Chinese folk songs into 10 major categories, and used 500 Chinese folk songs in our experiment. 74 features have been extracted from audio files of the songs, and classified by an audio classifier on SVM. The...
This paper presents a robust invariant descriptor for symbol-based image recognition and retrieval. A modified Hough-based Transform is used to extract parameter space information (i.e., position data and angular data) from a symbol image to derive an invariant descriptor. The proposed descriptor provides a compact representation of a symbol image that can be evaluated efficiently. The extracted descriptor...
Computer algebra system (CAS) applications are mathematical applications developed with the purpose of solving mathematical problems which are too difficult or even impossible to solve by hand. Modern versions of CAS applications are known for their rather large set of features such as support for graphical representations of results, symbolic manipulation, big-integer calculations, and complex-number...
A kind of dynamic opcode n-gram software birthmark is proposed in this paper based on Myles' software birthmark (in which static opcode n-gram set is regarded as the software birthmark). The dynamic opcode n-gram set is regarded as the software birthmark which is extracted from the dynamic executable instruction sequence of the program. And the new birthmark can not only keep the advantages of feature...
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