35278447
An Investigation on Transformation-based Error-driven Learning Algorithm for Chinese Noun Phrase Extraction
Noun phrases are commonly used for generating index terms for information retrieval systems. Therefore, we need an effective noun phrase extraction method. In this paper, we propose an approach to extract maximal noun phrases from Chinese text. Although previous studies have been proposed to extract noun phrases, most of them are only applicable to Western languages. To the best of our knowledge, very few has handled Chinese text. Many existing approaches for Western languages made use of statistical methods. However, due to the complicated structure of maximal Chinese noun phrase, pure statistical approaches are not effective. We attempt to improve the performance of a statistical method by integrating it with the transformation-based error-driven learning (TEL) technique. Our methodology includes two modules. The first module applies a statistical method to extract Chinese noun phrases. The performance of this approach, in terms of precision and recall, is investigated. The second module applies the TEL algorithm to further refine the output of the first module. The TEL algorithm automatically learns a set of transformation rules to fix the errors that are obtained through comparing the output of the first module with the correctly annotated corpus. The learned rules can be applied to sentences in any corpus one by one to correct the errors. The TEL algorithm is shown to be effective in improving the precision.
37472111
Extending the superimposed codeword indexing scheme to handle incomplete information
In order to use Prolog as a basis for database applications, techniques are required for rapid retrieval of clauses from large data sets. Various researchers have contributed to the development of indexing strategies for this purpose. One such strategy is known as superimposed codeword+mask bits (SCW+MB). One extension of Prolog which is useful in the development of deductive databases is the ability to handle incomplete information. A form of incomplete information based on sets has been introduced and used in a deductive database system. In order to provide efficient access to clauses containing incomplete information, existing strategies need to be adapted accordingly. This paper presents an extension to the SCW+MB algorithm to cover incomplete information, and describes how this can be realized in hardware.
45209699
A Workflow Model for Chinese Business Processes
This paper proposes a new workflow model (MAWM) targeted at Chinese business processing. The cultural dependent characteristics of Chinese business processes are identified and taken into account in the MAWM model. MAWM adopts a decentralized modeling style based on the conventional business perspective on labor division and cooperation. This idea is reflected in the concept of agent-workflow. Activity-based and communication-based modeling methods are integrated in the process model. They are used to model different types of business activities. In addition, the model is formalized using Process Algebra and a simplified algorithm is proposed for safety verification of workflow processes.
1165688
A Chinese dictionary construction algorithm for information retrieval
In this article we propose a method for constructing, from raw Chinese text, a statistics-based automatic dictionary. The method makes use of local statistical information (i.e., data within a document) to identify and discard repeated string patterns, which, at an earlier stage, were substrings of legitimate words. Global statistical information (which exists throughout the entire corpus) and contextual constraints are then used for further filtering. The method can be used to alleviate the out-of-vocabulary (OOV) problem, which is commonly found in dictionary-based natural language information-processing applications, e.g., word segmentation. It can handle text corpora dynamically and, further, it does not impose any strict requirements on the size and quality of the training corpora. Based on our method, we constructed Chinese dictionaries from different Chinese corpora. We then applied the words in the constructed dictionaries to indexing in information retrieval (IR). Retrieval performance using such indexes was compared to the same, but based on indexes produced by static dictionaries. Three Chinese corpora using various character-encoding schemes and language styles were used in the experiments. The results show that retrieval using indexes based on the constructed dictionary is effective. This implies that fully automatic Chinese dictionary construction based on dynamic data sources, e.g., from the Internet, for the purposes of IR is feasible. Drawing on the experiment, we were able to make some interesting observations: (1) using only a portion of a dictionary is enough to produce good retrieval performance, e.g., a dictionary consisting of only the 500 highest-frequency strings extracted from the NTCIR 2 Chinese corpus produced as good a retrieval result as using a more complete dictionary with over 100K entries; and (2) complete word segmentation is not a strict requirement for achieving practical information retrieval.
12876616
A Design of Temporal Event Extraction from Chinese Financial News
This paper presents an information system for Chinese Information Extraction from Financial news (CHIEF). The ultimate target of the system is to extract information concerning the occurrence time and places of the financial activities in the different companies from a local Hong Kong newspaper, namely (Tao Kung Pao). To facilitate event extraction purpose, two groups of templates were defined, i.e. the company related and company restructuring templates. They are used to select the desired information for each type of financial activities, such as (bankruptcy) or (merge). Each specific event is then represented using a frame-based knowledge structure. Two types of slots are embedded in each frame: they are the activity- and time-related slots. Based on these slots, multiple activities are interconnected according to their entity relations, temporal relations or the deduced relations. Effectively, CHIEF is a question-answering system designed for handling the company related queries, event based queries, temporal queries and complex queries in a finance domain.
7493579
CLARE—a Prolog database machine
The CLAuse Retrieval Engine (CLARE) is a coprocessor system which based on two-stage filtering, for handling large sets of disc resident clauses in Prolog database applications. The overall architecture and the timing measurements of the first stage CLARE hardware are reported. The timing measurements shows that the first stage CLARE hardware can perform search operations on data transferring at a rate up to 4.5 million double bytes per second.
7622452
Tracking based motion segmentation under relaxed statistical assumptions
We present a novel and efficient motion segmentation and tracking algorithm that follows the shift and align paradigm. We introduce two statistical tests to evaluate the similarity of aligned image pixels or patches and we use them to determine the spatial extend of each segment. The one statistical test is fast and accurate when the noise is moderate and the other employs a sophisticated noise model involving the Mahalanobis distance to handle correlated noise. Direct computation of the Mahalanobis distance is prohibitively expensive so we apply the Sherman-Morrison-Woodbury identity and amortization to reduce the cost by several orders of magnitude. We tested both versions of the algorithm on a variety of image sequences (indoor and outdoor, real and synthetic, constant and varying lighting, stationary and moving camera, one of them with known ground truth) with very good results.
1578831
Pose estimation for augmented reality applications using genetic algorithm
This paper describes a genetic algorithm that tackles the pose-estimation problem in computer vision. Our genetic algorithm can find the rotation and translation of an object accurately when the three-dimensional structure of the object is given. In our implementation, each chromosome encodes both the pose and the indexes to the selected point features of the object. Instead of only searching for the pose as in the existing work, our algorithm, at the same time, searches for a set containing the most reliable feature points in the process. This mismatch filtering strategy successfully makes the algorithm more robust under the presence of point mismatches and outliers in the images. Our algorithm has been tested with both synthetic and real data with good results. The accuracy of the recovered pose is compared to the existing algorithms. Our approach outperformed the Lowe's method and the other two genetic algorithms under the presence of point mismatches and outliers. In addition, it has been used to estimate the pose of a real object. It is shown that the proposed method is applicable to augmented reality applications.
35666520
Automatic Lyrics Alignment on Popular Music
53788593
A fast recursive 3D model reconstruction algorithm for multimedia applications
A recursive two-step method to recover structure and motion from image sequences based on Kalman filtering is described in this paper. The algorithm consists of two major steps. The first step is an extended Kalman filter for the estimation of the object's pose. The second step is a set of extended Kalman filters, one for each model point, for refining the positions of the model features in the 3D space. The initial guess is a planar model formed under the assumption of orthographic projection on the first image. These two steps alternate from frames to frames. The planar model converges to the final structure as the image sequence is scanned sequentially. The performance of the algorithm is demonstrated with both synthetic data and real world objects. Comparisons with different approaches have been performed and show that our method is more efficient.
6767443
Report from the 2nd International Workshop on Software Engineering Course Projects (SWECP 2005)
This paper reports on the activities and results from the 2nd International Workshop on Software Engineering Course Projects (SWECP 2005), which was held on October 18, 2005 in Toronto, Canada. Creating software engineering course projects for undergraduate students is a challenging task. The instructor must carefully balance the conflicting goals of academic rigor and industrial relevance. Some of the fundamental characteristics of software engineering projects (e.g., team-based, large-scale, long-lived) are difficult to realize within the constraints of a university course in a single semester. This is particularly true when dealing with young students who may lack the real-world experience needed to appreciate some of the more subtle aspects of software engineering. This workshop explored how educators and industry can work together to develop a more rewarding educational experience for all stakeholders involved. Several key themes emerged from the workshop, including the importance of forming teams that are fair and balanced, the challenges in selecting a project that engages the students and meets the goals of the course, and the need for knowledge transfer amongst instructors.