4516498
Using Instant Messaging to Provide an Intelligent Learning Environment
Instant Messaging enables learners and educators to interact in an on-line environment. In this paper, we propose an intelligent ChatBot system, based on instant messaging, for student on-line coaching in an English learning environment. The proposed ChatBot facilitates synchronous communication with students by using ready reference materials including, dictionaries, authorized conversation material with speaking, and a question-answering function. The agent records and analyzes conversations so that the teacher can assess students' progress. Our contribution in this paper is that we integrate the NLP Tool and AIML into an instant messaging-based ChatBot for English as a Second Language programs.
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.
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.
12690340
A knowledge-based approach to citation extraction
Integration of the bibliographical information of scholarly publications available on the Internet is an important task in academic research. To accomplish this task, accurate reference metadata extraction for scholarly publications is essential for the integration of information from heterogeneous reference sources. In this paper, we propose a knowledge-based approach to literature mining and focus on reference metadata extraction methods for scholarly publications. We adopt an ontological knowledge representation framework called INFOMAP to automatically extract the reference metadata. The experimental results show that, by using INFOMAP, we can extract author, title, journal, volume, number (issue), year, and page information from different reference styles with a high degree of accuracy. The overall average field accuracy of citation extraction for a bioinformatics dataset is 97.87% for six reference styles.
32109322
RIBRA-An Error-Tolerant Algorithm for the NMR Backbone Assignment Problem
We develop an iterative relaxation algorithm, called RIBRA, for NMR protein backbone assignment. RIBRA applies nearest neighbor and weighted maximum independent set algorithms to solve the problem. To deal with noisy NMR spectral data, RIBRA is executed in an iterative fashion based on the quality of spectral peaks. We first produce spin system pairs using the spectral data without missing peaks, then the data group with one missing peak, and finally, the data group with two missing peaks. We test RIBRA on two real NMR datasets: hb-SBD and hbLBD, and perfect BMRB data (with 902 proteins) and four synthetic BMRB data which simulate four kinds of errors. The accuracy of RIBRA on hbSBD and hbLBD are 91.4% and 83.6%, respectively. The average accuracy of RIBRA on perfect BMRB datasets is 98.28%, and 98.28%, 95.61%, 98.16% and 96.28% on four kinds of synthetic datasets, respectively.
87458683
A Knowledge-Based Approach to Protein Local Structure Prediction
Local structure prediction can facilitate ab initio structure prediction, protein threading, and remote homology detection. However, previous approaches to local structure prediction suffer from poor accuracy. In this paper, we propose a knowledge-based prediction method that assigns a measure called the local match rate to each position of an amino acid sequence to estimate the confidence of our approach. To remedy prediction results with low local match rates, we use a neural network prediction method. Then, we have a hybrid prediction method, HYPLOSP (HYbrid method to Protein LOcal Structure Prediction) that combines our knowledge-based method with a neural network method. We test the method on two different structural alphabets and evaluate it by QN, which is similar to Q3 in secondary structure prediction. The experimental results show that our method yields a significant improvement over previous studies.
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.
9763838
Generative, discriminative, and ensemble learning on multi-modal perceptual fusion toward news video story segmentation
News video story segmentation is a critical task for automatic video indexing and summarization. Our prior work has demonstrated promising performance by using a generative model, called maximum entropy (ME), which models the posterior probability given the multi-modal perceptual features near the candidate points. In this paper, we investigate alternative statistical approaches based on discriminative models, i.e. support vector machine (SVM), and ensemble learning, i.e. boosting. In addition, we develop a novel approach, called BoostME, which uses the ME classifiers and the associated confidence scores in each boosting iteration. We evaluated these different methods using the TRECVID 2003 broadcast news data set. We found that SVM-based and ME-based techniques both outperformed the pure boosting techniques, with the SVM-based solutions achieving even slightly higher accuracy. Moreover, we summarize extensive analysis results of error sources over distinctive news story types to identify future research opportunities
6232755
Algorithms for minimum covering by cliques and maximum clique in claw-free perfect graphs
An algorithm is given for determining a minimum cardinality clique cover ongraphs that do not contain claws, odd holes or odd anti-holes. These graphs are also shown to be perfect so that we obtain a new proof of the strong perfect graph theorem for claw-free graphs. A by-product of our analysis is an algorithm for determining a maximum cardinality clique on claw-free perfect graphs.
10542450
Capturing dynamic memory reference behavior with adaptive cache topology
Memory references exhibit locality and are therefore not uniformly distributed across the sets of a cache. This skew reduces the effectiveness of a cache because it results in the caching of a considerable number of less-recently-used lines which are less likely to be re-referenced before they are replaced. In this paper, we describe a technique that dynamically identifies these less-recently-used lines and effectively utilizes the cache frames they occupy to more accurately approximate the global least-recently-used replacement policy while maintaining the fast access time of a direct-mapped cache. We also explore the idea of using these underutilized cache frames to reduce cache misses through data prefetching. In the proposed design, the possible locations that a line can reside in is not predetermined. Instead, the cache is dynamically partitioned into groups of cache lines. Because both the total number of groups and the individual group associativity adapt to the dynamic reference pattern, we call this design the adaptive group-associative cache. Performance evaluation using trace-driven simulations of the TPC-C benchmark and selected programs from the SPEC95 benchmark suite shows that the group-associative cache is able to achieve a hit ratio that is consistently better than that of a 4-way set-associative cache. For some of the workloads, the hit ratio approaches that of a fully-associative cache.
17900842
Fast cache access with full-map block directory
There are two concurrent paths in a typical cache access -one through the data array and the other through the tag array. In most cases, the path through the tag array is significantly longer than that through the data array. In this paper, we propose a new scheme that exploits this imbalance in the tag and data paths to improve overall cache performance. Under this scheme, an additional tag directory, the full-map block directory, is used to provide an alternate tag path to speed up cache access for almost all the memory requests. This scheme is based on the observation that spatial locality exists on a cache line basis i.e. cache lines near one another tend to be referenced together. Performance evaluation using the TPC-C benchmark and the SPEC92 benchmark suite demonstrates that this scheme has the potential to improve overall system performance by more than 20%.