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This paper compares the performance of keyword and machine learning-based chest x-ray report classification for Acute Lung Injury (ALI). ALI mortality is approximately 30 percent. High mortality is, in part, a consequence of delayed manual chest x-ray classification. An automated system could reduce the time to
Markov Model/ Artificial Neural Network (HMM/ANN) keyword spotting framework. The feature extraction method used was Mel-Frequency Cepstral Coefficients (MFCC). The ANN is a 3-layer feedforward neural network using Multi-Layer Perceptron (MLP). In recognizing the words, an HMM decoder was used which implemented the Viterbi
Language model adaptation using text data downloaded from the WWW is an efficient way to train a topic-specific LM. We are developing an unsupervised LM adaptation method using data in the Web. The one key point of unsupervised Web-based LM adaptation is how to select keywords to compose the search query. In this
This paper presents a corpus-based approach for extracting keywords from a text written in a language that has no word boundary. Based on the concept of Thai character cluster, a Thai running text is preliminarily segmented into a sequence of inseparable units, called TCCs. To enable the handling of a large-scaled
In cross-language information retrieval (CLIR), the query sentence is often combined with a series of query keywords, rather than a complete natural sentence. Lack of necessary contextual syntactic information in such a query sentence makes it impossible to achieve a unique translation of the query sentence with
Audio mining is a speaker independent speech processing technique and is related to data mining. Keyword spotting plays an important role in audio mining. Keyword spotting is retrieval of all instances of a given keyword in spoken utterances. It is well suited to data mining tasks that process large amount of speech
designed and implemented to resolve the problem of crossing language queries and retrieving images processes. It can greatly reduce lot of time and effort for the search. The experiments on diverse queries on Yahoo images search have shown that the proposed scheme can improve the images results for non-English keyword
This paper presents a text query-based method for keyword spotting from online Chinese handwritten documents. The similarity between a text word and handwriting is obtained by combining the character similiarity scores given by a character classifier. To overcome the ambiguity of character segmentation, multiple
approach has a limit as only the annotations of found images during the interaction are updated. In this paper we introduce a novel method of semi-automatic annotation. The method is using visual feature representations of keywords which are improved during the region-based relevance feedback. The experiments show that this
This paper presents our recent attempt to make a super-large scale spoken-term detection system, which can detect any keyword uttered in a 2,000-hour speech database within a few seconds. There are three problems to achieve such a system. The system must be able to detect out-of-vocabulary (OOV) terms (OOV problem
Keywords are indexed automatically for large-scale categorization corpora. Indexed keywords of more than 20 documents are selected as seed words, thus overcoming subjectivity of selecting seed words in clustering; at the same time, clustering is limited to particular category corpora and keywords indexed feature
This paper presents an audio keywords detection method for highlight retrieval in basketball video. The keywords contain shoes squeaking sound, speech, cheer, long whistle and short whistle, which correspond to basketball game events. After feature analysis, the Simple Excellent Feature Combination based on Pearson
structure of keywords. First, this paper proposes the extraction method of important keywords in their opinions based on the modification relationships. Next, it clusters the respondents interactively on visible space using MDS. Finally, it shows their opinions using HK Graph which can visualize the relationship among words
The complex network theory is widely used in the field of keyword extraction. Through analyzing the insufficient of keyword extraction algorithms using traditional complex network, this paper proposes a new method to extract Chinese keyword based on semantically weighted network. On the basis of K-nearest neighbor
This paper focuses on setting up a question-answering oriented biomedical domain, and it applies several different approaches to the different processing phases. Firstly, it uses shallow parser to identify the types of questions and extract the keywords, and the keywords are expanded with UMLS for the purpose of
Along with the rapid growth of the xml data quantity on the Internet, the xml data retrieval research has attracted more and more attention. The searching algorithm based on key words is a research hotspot in this field. We present a context-based layered intersection scan algorithm (CLISA), which uses the context
In the era of information explosion, information retrieval has become a bottleneck in information sharing and integration. However currently, the existing information retrieval methods are mainly based on keyword matching, which can not fully take advantage of the information context and potential knowledge. All of
This paper proposes a system of retrieving English sentences by utilizing linguistically structural information. The userpsilas query consists of a sequence of keywords. The system automatically identifies dependency relations between occurrences of the keywords in sentences and classifies the sentences according to
Previous approaches of emotion recognition from text were mostly implemented under keyword-based or learning-based frameworks. However, keyword-based systems are unable to recognize emotion from text with no emotional keywords, and constructing an emotion lexicon is a tough work because of ambiguity in defining all
Soccer highlight detection is an active research topic in recent years. In this paper, we present our effort to detect an important audio keyword - excited commentator speech, which contributes to a state-of-the-art soccer highlight extraction system. We propose an approach of using statistical classifier based on
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