9113597
Designing an ontology-based intelligent tutoring agent with instant messaging
The rapid growth of the Internet and instant messaging (IM) offers new opportunities as well as challenges to both educators and students. In this paper, we propose an intelligent tutoring agent (ITA) that uses the ontology, INFOMAP, and question answering techniques through the instant messaging platform for the "operating system " course. The ITA embeds the above techniques in the teaching process and plays the role of a tutoring agent to help a teacher track, record, and understand a student's status. The ITA interface can interpret natural language to facilitate communication between the student and the tutor. Student can query and learn the concept of "operating system" through MSN Messenger, which ITA adopts as the communication protocol. The proposed ITA is accessible by adding the contact ID: iaslita@hotmail.com to the MSN Messenger contacts list.
5724385
An iterative relaxation technique for the NMR backbone assignment problem
NMR spectroscopy is one of the popular experiments to determine protein structures. An important stage of protein structure determination by using NMR is protein backbone resonance assignment (or backbone assignment for short). Due to the messiness and disorder of NMR spectral data, backbone assignment is usually a tedious and time-consuming manual work. This raises a great interest in developing an efficient and automatic method to perform backbone assignment. An iterative algorithm is proposed that is equipped with two operations: grouping and linking. Grouping is responsible for peak picking and part of connectivity determination. Ideally, those peaks with the same H/sup N/ and N chemical shifts can be grouped together; peaks belonging to the same group can be used to determine the order of two consecutive spin systems. However, in real situation, grouping is a difficult task due to false positives and false negatives. We sometimes add hypothetic peaks to tackle false negatives and use linking operation to remove false positives. Linking is responsible for part of connectivity determination and backbone assignment. Given a protein sequence and partial connectivity information, we try to link connected spin systems as much as possible. False positive spin systems may create conflicts in the linking stage. To find a good assignment on a noisy dataset, the backbone assignment problem is modeled as a maximum independent set problem. Although the problem is NP-complete, there are heuristic methods that obtain pretty good results.
1251407
Reference metadata extraction using a hierarchical knowledge representation framework
The integration of bibliographical information on scholarly publications available on the Internet is an important task in the academic community. Accurate reference metadata extraction from such publications is essential for the integration of metadata from heterogeneous reference sources. In this paper, we propose a hierarchical template-based reference metadata extraction method for scholarly publications. We adopt a hierarchical knowledge representation framework called INFOMAP, which automatically extracts metadata. The experimental results show that, by using INFOMAP, we can extract author, title, journal, volume, number (issue), year, and page information from different kinds of reference styles with a high degree of precision. The overall average accuracy is 92.39% for the six major reference styles compared in this study.
5367915
A Maximum Entropy Approach to Biomedical Named Entity Recognition
Machine learning approaches are frequently used to solve name entity (NE) recognition (NER). In this paper we propose a hybrid method that uses maximum entropy (ME) as the underlying machine learning method incorporated with dictionary-based and rule-based methods for post-processing. Simply using ME for NER, inaccurate boundary detection of NEs and misclassification may occur. Some NEs are partially recognized by ME. In the post-processing stage, we use dictionary-based and rule-based methods to extend boundary of partially recognized NEs and to adjust classification. We use GENIA corpus 3.01 to conduct 10-fold cross-verification experiments. To evaluate the performance, we consider the longest NE annotations. We evaluate our approach using standard precision (P), recall (R), and F-score, where F-score is defined as 2PR/(P+R). The precision, recall and F-score ([P, R, F]) of our ME module for overall 23 categories is [0.512, 0.538, 0.525], and after the post-processing the performance becomes [0.729, 0.711, 0.72] for [P, R, F]. For protein, DNA and RNA classes, our method achieves [P, R, F] of [0.77, 0.80, 0.785], [0.653, 0.748, 0.7], and [0.716, 0.788, 0.752], respectively. The post-processing stage significantly improves the performance of our ME-based NER module.
341424
Domain Event Extraction and Representation with Domain Ontology
With domain ontology, a meaningful index of document indexing, such as the domain events structure in this paper, can be defined. Since the construction of domain ontology is costly, an automatic domain ontology acquisition is preferred. We find that named entity can be a clue of domain event acquisition from the training corpus. Therefore , we add the named entity recognition module into the automatic domain ontology acquisition process. Thus, a subject-verb-object-modifier (SVOM) indexing can be constructed. Our experimental results demonstrate that the automatic event extraction and ontology acquisition can be good resources for text categorization and further information processing.
17603178
A Linear Time Algorithm for Finding a Maximal Planar Subgraph Based on PC-Trees
In Shih & Hsu, a planarity test was introduced utilizing a data structure called PC-trees, generalized from PQ-trees. They illustrated that a PC-tree is more natural in representing planar graphs. Their algorithm starts by constructing a depth-first-search tree and adds all back edges to a vertex one by one. An important feature in the S&H algorithm is that, at each iteration, at most two terminal nodes need to be computed and the unique tree path between these two nodes provides essentially the boundary path of the newly formed biconnected component. 
 
In this paper we modify their PC-tree algorithm and introduce the deferred planarity test (DPT), which has the added benefit of finding a maximal planar subgraph (MPS) in linear time when the given graph is not planar. DPT is an incremental algorithm, which only computes a partial terminal path at each iteration. DPT continually deletes back edges that could create a violation to the formation of those partial terminal paths so that, at the end, the subgraph constructed is guaranteed to be planar. 
 
The key to the efficiency of the S&H and the DPT algorithms lies in their management on the creation and destruction of biconnected components in which the PC-tree plays a major role. Previously, there have been reports that the MPS problem can be solved in linear time. However, there was no concrete data structure realizing them.
17259799
The performance impact of I/O optimizations and disk improvements
In this paper, we use real server and personal computer workloads to systematically analyze the true performance impact of various I/O optimization techniques, including read caching, sequential prefetching, opportunistic prefetching, write buffering, request scheduling, striping, and short-stroking. We also break down disk technology improvement into four basic effects--faster seeks, higher RPM, linear density improvement, and increase in track density--and analyze each separately to determine its actual benefit. In addition, we examine the historical rates of improvement and use the trends to project the effect of disk technology scaling. As part of this study, we develop a methodology for replaying real workloads that more accurately models I/O arrivals and that allows the I/O rate to be more realistically scaled than previously. We find that optimization techniques that reduce the number of physical I/Os are generally more effective than those that improve the efficiency in performing the I/Os. Sequential prefetching and write buffering are particularly effective, reducing the average read and write response time by about 50% and 90%, respectively. Our results suggest that a reliable method for improving performance is to use larger caches up to and even beyond 1% of the storage used. For a given workload, our analysis shows that disk technology improvement at the historical rate increases performance by about 8% per year if the disk occupancy rate is kept constant, and by about 15% per year if the same number of disks are used. We discover that the actual average seek time and rotational latency are, respectively, only about 35% and 60% of the specified values. We also observe that the disk head positioning time far dominates the data transfer time, suggesting that to effectively utilize the available disk bandwidth, data should be reorganized such that accesses become more sequential.
16227528
Fast image retrieval using color-spatial information
Abstract. In this paper, we present an image retrieval system that employs both the color and spatial information of images to facilitate the retrieval process. The basic unit used in our technique is a single-colored cluster, which bounds a homogeneous region of that color in an image. Two clusters from two images are similar if they are of the same color and overlap in the image space. The number of clusters that can be extracted from an image can be very large, and it affects the accuracy of retrieval. We study the effect of the number of clusters on retrieval effectiveness to determine an appropriate value for “optimal'' performance. To facilitate efficient retrieval, we also propose a multi-tier indexing mechanism called the Sequenced Multi-Attribute Tree (SMAT). We implemented a two-tier SMAT, where the first layer is used to prune away clusters that are of different colors, while the second layer discriminates clusters of different spatial locality. We conducted an experimental study on an image database consisting of 12,000 images. Our results show the effectiveness of the proposed color-spatial approach, and the efficiency of the proposed indexing mechanism.
269822
Visual Cue Cluster Construction via Information Bottleneck Principle and Kernel Density Estimation
Recent research in video analysis has shown a promising direction, in which mid-level features (e.g., people, anchor, indoor) are abstracted from low-level features (e.g., color, texture, motion, etc.) and used for discriminative classification of semantic labels. However, in most systems, such mid-level features are selected manually. In this paper, we propose an information-theoretic framework, visual cue cluster construction (VC3), to automatically discover adequate mid-level features. The problem is posed as mutual information maximization, through which optimal cue clusters are discovered to preserve the highest information about the semantic labels. We extend the Information Bottleneck framework to high-dimensional continuous features and further propose a projection method to map each video into probabilistic memberships over all the cue clusters. The biggest advantage of the proposed approach is to remove the dependence on the manual process in choosing the mid-level features and the huge labor cost involved in annotating the training corpus for training the detector of each mid-level feature. The proposed VC3 framework is general and effective, leading to exciting potential in solving other problems of semantic video analysis. When tested in news video story segmentation, the proposed approach achieves promising performance gain over representations derived from conventional clustering techniques and even the mid-level features selected manually.
38278026
A Simple Test for the Consecutive Ones Property
A (0,1)-matrix satisfies the consecutive ones property if there exists a column permutation such that the ones in each row of the resulting matrix are consecutive. Booth and Lueker (1976, J. Comput. System Sci.13, 335?378) designed a linear time-testing algorithm for this property based on a data structure called “PQ-trees.” This procedure is quite complicated and the linear-time-amortized analysis is also rather involved. We developed an off-line linear time test for the consecutive ones property without using PQ-trees and the corresponding template matching, which makes ours considerably simpler. A simplification of the consecutive ones test will immediately simplify algorithms (and computer codes) for interval-graph and planar-graph recognition. Our approach is based on a decomposition technique that separates the rows into prime subsets, each of which admits essentially a unique column ordering that realizes the consecutive ones property. The success of this approach is based on finding a good “row ordering” to be tested iteratively.
931369
Improving cache performance with balanced tag and data paths
There are two concurrent paths in a typical cache access --- one through the data array and the other through the tag array. The path through the data array drives the selected set out of the array. The path through the tag array determines cache hit/miss and, for set-associative caches, selects the appropriate line from within the selected set. In both direct-mapped and set-associative caches, the path through the tag array is significantly longer than that through the data array. In this paper, we propose a path balancing technique help match the delays of the tag and data paths. The basic idea behind this technique is to employ a separate subset of the tag array to decouple the one-to-one relationship between address tags and cache lines so as to achieve a design that provides higher performance. Performance evaluation using both TPC-C and SPEC92 benchmarks shows that this path balancing technique offers impressive improvements in overall system performance over conventional cache designs. For TPC-C, improvements in the range of 6% to 28% are possible.