1260337
An Improved k-Nearest Neighbor Algorithm for Text Categorization
k is the most important parameter in a text categorization system based on k-Nearest Neighbor algorithm (kNN).In the classification process, k nearest documents to the test one in the training set are determined firstly. Then, the predication can be made according to the category distribution among these k nearest neighbors. Generally speaking, the class distribution in the training set is uneven. Some classes may have more samples than others. Therefore, the system performance is very sensitive to the choice of the parameter k. And it is very likely that a fixed k value will result in a bias on large categories. To deal with these problems, we propose an improved kNN algorithm, which uses different numbers of nearest neighbors for different categories, rather than a fixed number across all categories. More samples (nearest neighbors) will be used for deciding whether a test document should be classified to a category, which has more samples in the training set. Preliminary experiments on Chinese text categorization show that our method is less sensitive to the parameter k than the traditional one, and it can properly classify documents belonging to smaller classes with a large k. The method is promising for some cases, where estimating the parameter k via cross-validation is not allowed.
34801552
Profile-based event tracking
In this research, we focus on tracking topics that originate and evolve from a specific event. Intuitively, a few key elements of a target event, such as date, location, and persons involved, would be enough for making a decision on whether a test story is on-topic. Consequently, a profile-based event tracking method is proposed. We attempt to build an event profile from the given on-topic stories by robust information retrieval technologies. A feature selection metric and a recognized event clause are utilized to determine most (if not all) key semantic elements of the target event. Preliminary experiments on the TDT2 mandarin corpus show that this profile-based event tracking method is promising.
195606600
CTEMP: a chinese temporal parser for extracting and normalizing temporal information
Temporal information is useful in many NLP applications, such as information extraction, question answering and summarization. In this paper, we present a temporal parser for extracting and normalizing temporal expressions from Chinese texts. An integrated temporal framework is proposed, which includes basic temporal concepts and the classification of temporal expressions. The identification of temporal expressions is fulfilled by powerful chart-parsing based on grammar rules and constraint rules. We evaluated the system on a substantial corpus and obtained promising results.
10610312
Semantic sports video analysis: approaches and new applications
In this paper, we show that event-based semantic analysis of sports video can be achieved through two major classes of methods: approaches using deterministic reasoning and approaches depending on probabilistic inference. Deterministic approaches depend on an explicit description of an event and an explicit representation of the event in terms of low-level aural-visual features that can be automatically detected. Probabilistic approaches are based on some proper state/transition models whose parameters are learnt through labeled training sequences. We first discuss the pros and cons of the two classes of approaches. Next, we present algorithms of these two types for a new application, automatic analysis of coaching video (which is different from sports broadcast programs that have been subject of most prior work).
3208295
Price-based resource allocation in wireless ad hoc networks
The shared-medium multi-hop nature of wireless ad hoc networks poses fundamental challenges to the design of an effective resource allocation algorithm to maximize the aggregated utility of flows, while maintaining basic fairness among multiple flows. When previously proposed scheduling algorithms have been shown to perform well in providing fair shares of bandwidth among single-hop wireless flows, they did not consider multi-hop flows with an end-to-end perspective. Moreover, the resource allocation strategies employed in the wireline network can not be applied directly in the context of ad hoc networks due to the unique characteristic of location dependent contention and spatial reuse of the shared wireless channel. In this paper, we propose a price-based resource allocation model to achieve maximized aggregated utility (i.e., social welfare) of flows. Our original contributions are: First, we propose to use maximal clique-associated shadow prices for wireless channel access coordination, rather than link-associated price for wireline link access arbitration. Second, we present a new pricing policy for end-to-end multi-hop flow. Using this model, different fairness goals can be realized in ad hoc networks for end-to-end flows. With a two-tier distributed and iterative algorithm, scarce channel capacity is allocated fairly among multi-hop flows from an end-to-end perspective, using shadow prices as the mechanism to arbitrate channel access. Through extensive analysis and simulation results, we show that our proposed algorithm is able to fairly distribute resources among multi-hop flows, while simultaneously maximizing the aggregated utility of flows globally.
3580064
Bit section instruction set extension of ARM for embedded applications
Programs that manipulate data at subword level, i.e. bit sections within a word, are common place in the embedded domain. Examples of such applications include media processing as well as network processing codes. These applications spend significant amounts of time packing and unpacking narrow width data into memory words. The execution time and memory overhead of packing and unpacking operations can be greatly reduced by providing direct instruction set support for manipulating bit sections.In this paper we present the Bit Section eXtension (BSX) to the ARM instruction set. We selected the ARM processor for this research because it is one of the most popular embedded processor which is also being used as the basis of building many commercial network processing architectures. We present the design of BSX instructions and their encoding into the ARM instruction set. We have incorporated the implementation of BSX into the Simplescalar ARM simulator from Michigan. Results of experiments with programs from various benchmark suites show that by using BSX instructions the total number of instructions executed at runtime by many transformed functions are reduced by 4.26% to 27.27% and their code sizes are reduced by `1.27% to 21.05%.
8595308
Experiences with MPEG-4 multimedia streaming
With the advent of next-generation multimedia technologies such as very-low bit rate MPEG-4 codec, multimedia streaming of high-quality video and audio has become a near-term reality. The high compression ratio and error resilience offered by the MPEG-4 standard promise near-term popularity for rich contents and exceptional quality to consumers over affordable Internet connections, such as xDSL, cable modem and 3G wireless networks. Audio and video streaming applications are at the center of such scenarios; and Quality-of-Service (QoS) support in such applications is critical to their widespread acceptance.To the best of our knowledge, there has been no existing open-source MPEG-4 multimedia streaming applications in the academic community, which leads to the lack of research results using MPEG-4 streaming, especially with respect to Quality-of-Service support. In this work, we have implemented an open-source MPEG-4 multimedia streaming testbed in IP-based networks. In this paper, we show our experiences and lessons learned with such a testbed. First, we describe the algorithms and solutions used in our implemention testbed, emphasizing several critical issues. Second, through extensive experiments, we demonstrate measurements of bandwidth requirements and data loss for streaming a set of multimedia samples with different bit rates over UDP, which is ubiquitously available in the TCP/IP protocol stack on all consumer operating systems. Finally, future work for further improvements is also discussed.
46149042
Data reconciliation for real-time optimization of an industrial coke-oven-gas purification process
Online optimization is more and more used in the chemical industry to run a process near its optimum operating condition by providing real-time computed optimal set-points to the distributed control system. Process measurements are necessary for these applications to determine the actual state of the process and to increase the accuracy of the model with parameter estimation techniques. However, these measurements usually contain random as well as gross errors which have to be identified and eliminated before the measurements are used for online optimization. In this contribution, a data reconciliation approach was integrated into an online optimization framework for the ammonia hydrogen sulfide circulation scrubbing, a common industrial coke-oven-gas purification process. We used a rigorous rate-based model to describe this reactive absorption and desorption process. To increase the accuracy of the model, we estimated several process parameters using a sequential parameter estimation approach. Data reconciliation was performed based on simple component balances to achieve model-consistent data and to identify measurement biases. The model was then validated online on a pilot plant by connecting the estimation package through the process control system. Based on the online measured data, operating cost minimization was carried out and the computed optimal set-points realized real-time. A satisfactory agreement between measured data and optimization was achieved.