669184
Generality of Texts
When searching or browsing, a user may be looking for either very general information or very specific information. We explored predictors for characterizing the generality of six encyclopedia texts. We had human subjects rank-order the generality of the texts. We also developed statistics from analysis of word frequency and from comparison to a set of reference terms. We found a statistically significant relationship between the human ratings of text generality and our automatic measure.
34278393
Interactive Causal Schematics for Qualitative Scientific Explanations
We present a simple model for describing causal processes. We apply it to generate schematics of complex scientific processes. Our interface allows users to select among causal threads and then to follow the state transitions of those explanations. Moreover, these schematics can provide a framework for interacting with texts.
6210562
Discriminative training and explicit duration modeling for HMM-based automatic segmentation
HMM-based automatic segmentation has been popularly used for corpus construction for concatenative speech synthesis. Since the most important reasons for the inaccuracy of HMM-based automatic segmentation are the HMM training criterion and duration control, we will study these particular issues. For the HMM training, we apply the discriminative training method and introduce a new criterion, named Minimum SeGmentation Error (MSGE). In this method, a loss function directly related to the segmentation error is defined, and parameter optimization is performed by the Generalized Probabilistic Descent (GPD) algorithm. For the duration control problem, we apply explicit duration models and propose a two-step-based segmentation method to solve the problem of computational cost, where the duration model is incorporated in a postprocessor procedure. From the experimental results, these two techniques significantly improve segmentation accuracy with different focuses, where the MSGE-based discriminative training focuses on improving the accuracy of sensitive boundary, i.e., a boundary where an error in segmentation is likely to cause a noticeable degradation in speech synthesis quality, and the explicit duration modeling focuses on eliminating large errors. After combining these two techniques, the error average was reduced from 6.86 ms to 5.79 ms on Japanese data, and from 8.67 ms to 6.61 ms on Chinese data. Simultaneously, the number of errors larger than 30 ms were reduced 25% and 51% on Chinese and Japanese data, respectively.
6184263
An Efficient Approach to Extracting Approximate Repeating Patterns in Music Databases
Pattern extraction from music strings is an important problem. The patterns extracted from music strings can be used as features for music retrieval or analysis. Previous works on music pattern extraction only focus on exact repeating patterns. However, music segments with minor differences may sound similar. The concept of the prototypical melody has therefore been proposed to represent these similar music segments. In musicology, the number of music segments that are similar to a prototypical melody implies the importance degree of the prototypical melody to the music work. In this paper, a novel approach is developed to extract all the prototypical melodies in a music work. Our approach considers each music segment as a candidate for the prototypical melody and uses the edit distance to determine the set of music segments that are similar to this candidate. A lower bounding mechanism, which estimates the number of similar music segments for each candidate and prunes the impossible candidates is designed to speed up the process. Experiments are performed on a real data set and the results show a significant improvement of our approach over the existing approaches in the average response time.
2511721
Fractal Modeling of IP Network Traffic at Streaming Speeds
This paper describes how to fit fractal models, online, on IP traffic data streams. Our approach relies on maintaining a sketch of the data stream and fitting straight lines: it yields algorithms that are fast, space-efficient, and accurate. We implemented our methods in AT&T’s Gigascope data stream management system, to demonstrate their practicality at streaming line speeds.
3736444
Domain-specific keyphrase extraction
Document keyphrases provide semantic metadata characterizing documents and producing an overview of the content of a document. They can be used in many text-mining and knowledge management related applications. This paper describes a Keyphrase Identification Program (KIP), which extracts document keyphrases by using prior positive samples of human identified domain keyphrases to assign weights to the candidate keyphrases. The logic of our algorithm is: the more keywords a candidate keyphrase contains and the more significant these keywords are, the more likely this candidate phrase is a keyphrase. To obtain prior positive inputs, KIP first populates its glossary database using manually identified keyphrases and keywords. It then checks the composition of all noun phrases of a document, looks up the database and calculates scores for all these noun phrases. The ones having higher scores will be extracted as keyphrases.
15215532
Estimating Answer Sizes for XML Queries
Estimating the sizes of query results, and intermediate results, is crucial to many aspects of query processing. In particular, it is necessary for effective query optimization. Even at the user level, predictions of the total result size can be valuable in "next-step" decisions, such as query refinement. This paper proposes a technique to obtain query result size estimates effectively in an XML database.Queries in XML frequently specify structural patterns, requiring specific relationships between selected elements. Whereas traditional techniques can estimate the number of nodes (XML elements) that will satisfy a node-specific predicate in the query pattern, such estimates cannot easily be combined to provide estimates for the entire query pattern, since element occurrences are expected to have high correlation.We propose a solution based on a novel histogram encoding of element occurrence position. With such position histograms, we are able to obtain estimates of sizes for complex pattern queries, as well as for simpler intermediate patterns that may be evaluated in alternative query plans, by means of a position histogram join (pH-join) algorithm that we introduce. We extend our technique to exploit schema information regarding allowable structure (the no-overlap property) through the use of a coverage histogram.We present an extensive experimental evaluation using several XML data sets, both real and synthetic, with a variety of queries. Our results demonstrate that accurate and robust estimates can be achieved, with limited space, and at a miniscule computational cost. These techniques have been implemented in the context of the TIMBER native XML database [22] at the University of Michigan.