322920
Introduction to the special issue on statistical language modeling
The goal of statistical language modeling (SLM) is to estimate the likelihood (or probability) of a word string. SLM is fundamental to many natural language applications like automatic speech recognition (ASR) [Jelinek 1990], statistical machine translation (SMT) [Brown et al. 1993], and Asian language text input [Gao et al. 2002a]. The research on SLM basically involves two main tasks: modeling and estimation. Modeling is to determine the structure of a statistical model; estimation is to determine the free parameters of the model using training data. SLM usually uses a parametric model with Maximum Likelihood Estimation (MLE) and various smoothing methods to tackle data sparseness problems. Different statistical models have been proposed in the past, but n-gram models (in particular, bigram and trigram models) still dominate SLM research. SLM has recently been demonstrated as an effective framework for a few new applications, such as question answering [Berger 2001], text summarization, paraphrasing [Barzilay and Lee 2004], and information retrieval [Croft and Lafferty 2003]. However, these new applications come with new challenges. For example, in the SLM approaches to information retrieval, a language model has to be trained on a single document, an extremely small training set; while in ASR, a language model is typically trained on a million word corpus. The recent development of related techniques stimulates new modeling and estimation methods that are beyond the scope of the traditional approaches. Two representative examples of such techniques are statistical parsing and discriminative training. With the ever-increasing popularity of SLM, we think that it is the right time to assemble a special issue reflecting recent advances in both its theory and applications. It __________________________________________________________________________________________
40804846
Question Answering in Webclopedia
SHAPE ADJECTIVE COLOR DISEASE TEXT NARRATIVE* GENERAL-INFO DEFINITION USE EXPRESSION-ORIGIN HISTORY WHY-FAMOUS BIO ANTECEDENT INFLUENCE CONSEQUENT CAUSE-EFFECT METHOD-MEANS CIRCUMSTANCE-MEANS REASON EVALUATION PRO-CON CONTRAST RATING COUNSEL-ADVICE To create the QA Typology, we analyzed 17,384 questions and their answers (downloaded from answers.com); see (Gerber, 2001). The Typology contains 94 nodes, of which 47 are leaf nodes; a section of it appears in Figure 2. Each Typology node has been annotated with examples and typical patterns of expression of both Question and Answer, as indicated in Figure 3 for Proper-Person. Question examples Question templates Who was Johnny Mathis' high school track coach? who be 's Who was Lincoln's Secretary of State? Who was President of Turkmenistan in 1994? who be of Who is the composer of Eugene Onegin? Who is the CEO of General Electric? Actual answers Answer templates Lou Vasquez, track coach of...and Johnny Mathis , of Signed Saparmurad Turkmenbachy [Niyazov], of president of Turkmenistan ...Turkmenistan’s President Saparmurad Niyazov... ’s ...in Tchaikovsky's Eugene Onegin... 's Mr. Jack Welch, GE chairman... ... ...Chairman John Welch said ...GE's | of related role-verb Figure 3. Portion of QA Typology node annotations for Proper-Person.
172983
The Effectiveness of Dictionary and Web-Based Answer Reranking
We describe an in-depth study of using a dictionary (WordNet) and web search engines (Altavista, MSN, and Google) to boost the performance of an automated question answering system, Webclopedia, in answering definition questions. The results indicate applying dictionary and web-based answer reranking together increase the performance of Webclopedia on a set of 102 TREC-10 definition questions by 25% in mean reciprocal rank score and 14% in finding answers in the top 5.
13476763
CPU/power-constrained mobile devices
Due to the limited processing capability, memory constraints, and the power budget of mobile clients, multimedia coders and/or decoders are often difficult to implement on wireless handheld PDAs. In this Universal Tuner project, we designed and implemented a wireless video streaming system that transcodes MPEG-1/2 videos or live TV broadcasting videos to the BW or indexed color Palm OS devices. In our system, the complexity of multimedia compression and decompression algorithms is adaptively partitioned between the encoder and decoder. A mobile client would selectively disable or reenable stages of the algorithm to adapt to the device's effective processing capability. Our variable-complexity strategy of selective disabling of modules supports graceful degradation of the complexity of multimedia coding and decoding into a mobile client's low-power mode, i.e. the clock frequency of its next-generation low power CPU has been scaled down to conserve power. We modified the structure of the standard motion-compensated DCT video codecs to implement a simplified the encoder on a PC server and the decoder on a complexity-constrained PDA viewing client.
42775921
ATM admission models of stochastic high level Petri nets based on hierarchical modeling
This paper presents a framework for modeling and analyzing ATM admission control using Stochastic High Level Petri Net (SHLPN). SHLPN is chosen because it is a powerful graphical and mathematical modeling tool that is able to handle concurrent, asynchronous, nondeterministic and stochastic events. In addition, there exists a set of well-developed performance analysis techniques for SHLPN. This paper uses a hierarchical modeling technique to specify complex ATM network mechanisms using a top-down approach. However, in analyzing the performance of the network, a bottom-up approach is adopted. To tackle the state space explosion problem, a SHLPN model is decomposed into submodels. These subnets are independently evaluated with all possible population which are then substituted by transitions with approximate equivalent performance in the original model. The technique is illustrated by modeling and evaluating a specific connection admission control policy.
1207322
Dynamic integrated scheduling of hard real-time, soft real-time, and non-real-time processes
Real-time systems are growing in complexity and real-time and soft real-time applications are becoming common in general-purpose computing environments. Thus, there is a growing need for scheduling solutions that simultaneously support processes with a variety of different timeliness constraints. Toward this goal we have developed the resource allocation/dispatching (RAD) integrated scheduling model and the rate-based earliest deadline (RBED) integrated multi-class real-time scheduler based on this model. We present RAD and the RBED scheduler and formally prove the correctness of the operations that RBED employs. We then describe our implementation of RBED and present results demonstrating how RBED simultaneously and seamlessly supports hard real-time, soft real-time, and best-effort processes.
6216194
The implementation and evaluation of fusion and contraction in array languages
Array languages such as Fortran 90, HPF and ZPL have many benefits in simplifying array-based computations and expressing data parallelism. However, they can suffer large performance penalties because they introduce intermediate arrays---both at the source level and during the compilation process---which increase memory usage and pollute the cache. Most compilers address this problem by simply scalarizing the array language and relying on a scalar language compiler to perform loop fusion and array contraction. We instead show that there are advantages to performing a form of loop fusion and array contraction at the array level. This paper describes this approach and explains its advantages. Experimental results show that our scheme typically yields runtime improvements of greater than 20% and sometimes up to 400%. In addition, it yields superior memory use when compared against commercial compilers and exhibits comparable memory use when compared with scalar languages. We also explore the interaction between these transformations and communication optimizations.
15301928
New techniques on deformed image motion estimation and compensation
In this paper, new techniques for deformed image motion estimation and compensation using variable-size block-matching are proposed, which can be applied to an image sequence compression system or a moving object recognition system. The motion estimation and compensation techniques have been successfully applied in the area of image sequence coding. Many research papers on improving the performance of these techniques have been published; many directions are proposed, which can all lead to better performance than the conventional techniques. Among them, both generalized block-matching and variable-size block-matching are successfully applied in reducing the data rate of compensation error and motion information, respectively. These two algorithms have their merits, but suffer from their drawbacks. Moreover, reducing the data rate in compensation error is sometimes increasing the data rate in motion information, or vice versa. Based on these two algorithms, we propose and examine several algorithms which are effective in reducing the data rate. We then incorporate these algorithms into a system, in which they work together to overcome the disadvantages to individual and keep their merits at the same time. The proposed system can optimally balance the amount of data rate in two aspects (i.e., compensation error and motion information). Experimental results show that the proposed system outweighs the conventional techniques. Since we propose a recovery operation which tries to recover the incorrect motion vectors from the global motion, this proposed system can also be applied to the moving object recognition in image sequences.