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topic detection and tracking     
相关语句
  话题识别与跟踪
     Topic detection and tracking (TDT) aims to develop a series of technologies for event based information organization, and hierarchical topic detection (HTD) is a new task of it.
     话题识别与跟踪(topic detection and tracking,TDT)旨在发展一系列基于事件的信息组织技术,层次化话题识别(hierarchical topic detection,HTD)是其中一项全新的任务定义形式.
短句来源
     Topic Detection and Tracking with a Developed Vector Space Model
     基于改进向量空间模型的话题识别与跟踪
短句来源
     Topic Tracking has grown out of the Topic Detection and Tracking (TDT).
     话题跟踪属于话题识别与跟踪(TDT)的一项子任务,是一种基于事件的信息组织技术。
     Object Migration Automaton(OMA) is a good method for Topic Detection and Tracking(TDT),because of its slow clustering,traditional OMA model can't satisfy the requirement in the aspect of real-time and incremental clustering.
     对象迁移自动机(OMA)是一种能够较好地解决话题识别与跟踪(TDT)中聚类问题的方法,但是,传统OMA模型由于聚类速度慢等缺点,难以满足TDT实时和增量聚类的要求.
短句来源
     Research on Topic Detection and Tracking
     话题识别与跟踪研究
短句来源
更多       
  话题发现与跟踪
     Hierarchical Topic Detection and Tracking and Implementation of System
     层次化话题发现与跟踪方法及系统实现
短句来源
     Topic Detection and Tracking is a research driven by evaluation,which intends to organize and utilize information stream of texts according to event.
     话题发现与跟踪是一项评测驱动的研究,旨在依据事件对语言文本信息流进行组织利用。
短句来源
     Since 1996,topic detection and tracking has obtained extensive attention and has encountered great challenge when making great progress.
     自1996年话题发现与跟踪评测启动以来,该研究受到普遍关注,取得巨大进步,也遇到诸多困难。
短句来源
     Topic Detection and Tracking is a research driven by evaluation, which intends to organize and utilize information stream of texts according to event.
     话题发现与跟踪是一项评测驱动的研究,旨在依据事件对语言文本信息流进行组织利用。
  话题检测与跟踪
     Development and Analysis of Technology of Topic Detection and Tracking
     话题检测与跟踪技术的发展与研究
     Topic Detection and Tracking (TDT) can help us to organize the potential information so that we can grasp all the details about events and the relations between events.
     话题检测与跟踪(TDT)技术可以帮助人们把分散的信息有效地汇集并组织起来,从整体上了解一个事件的全部细节以及该事件与其它事件之间的关系。
短句来源
     This research has grown out of the Topic Detection and Tracking (TDT) initiative sponsored by DARPA.
     它属于话题检测与跟踪的一项子任务。
短句来源
     The paper introduces the origin and history of the development of technology of topic detection and tracking, and makes remarks on its prospect. It also describes systemically the methods adopted by the current systems of topic detection and tracking, and makes comparison among their performance.
     本文介绍了话题检测与跟踪技术的由来和发展历程,并展望其应用前景,同时比较系统地介绍了现有的话题检测与跟踪系统主要采用的方法,并对其效果进行了比较。
  “topic detection and tracking”译为未确定词的双语例句
     Based on the above analysis of the news video, we present a probabilistic learning approach to model video news story for topic detection and tracking, In this approach, both content and time information of a news video is utilized to transcribe the news story into terms, which are divided into classes by their semantics.
     在对新闻视频分析的基础上,本文提出了视频新闻报道的一种表示方法,按照特征的语义把新闻报道表示为五个语义类,重点介绍了视频中场景特征的识别方法和用于视频中画面类型别的视频图像特征选择和提取方法,给出了一个基于边界方向直方图表示图像中纹理特征、并利用神经网络进行场景类型识别的算法。
短句来源
     The topic detection and tracking technology is just to meet this need.
     话题检测与追踪(Topic Detection and Trackina,TDT)技术正是为了满足这种需要,它研究如何检测新发生的事件并追踪事件后继发展动态的信息智能获取技术。
短句来源
     In the field of topic detection and tracking,since topics develop dynamically,topic excursion problem may appear in the tracking process.
     在话题追踪研究领域,由于话题是动态发展的,在追踪过程中会产生话题漂移的问题。
短句来源
     Topic detection is one of the tasks in TDT(Topic Detection and Tracking).
     文本的主题识别是TDT研究计划的核心任务之一。
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  topic detection and tracking
This can be seen as a complementary tool for topic detection and tracking applications.
      
Topic Detection and Tracking (TDT) is a research initiative that aims at techniques to organize news documents in terms of news events.
      
On the basis of the researches in the field of topic detection and tracking, we propose a model for hot topic discovery that will pick out hot topics by automatically detecting, clustering and weighting topics on the websites within a time period.
      
Topic detection and tracking, concept hierarchy, question answering and so on could also counted as text mining practice in general.
      
Topic detection and tracking using text-based techniques should prove to be very useful in generating program level summaries.
      
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As a new direction of research on n atural language processing,Topic Detection and Tracking aims at devel-oping t echnologies for event-based information organization,such as detecting stories on novel topic and tracking stories on known topics.Since1997,a series of evaluation on this research have been conducted,and made it more and more popu lar in Natural Language Processing,especially in information retrieval.The res earch on topic detection and tracking in China is just starting.Several issues about...

As a new direction of research on n atural language processing,Topic Detection and Tracking aims at devel-oping t echnologies for event-based information organization,such as detecting stories on novel topic and tracking stories on known topics.Since1997,a series of evaluation on this research have been conducted,and made it more and more popu lar in Natural Language Processing,especially in information retrieval.The res earch on topic detection and tracking in China is just starting.Several issues about this new research,such as task definition,history,technologies,and me a-surement ,are discussed.

作为自然语言处理一个新的研究方向,话题识别与跟踪旨在发展一系列基于事件的信息组织技术,以实现对新闻媒体信息流中新话题的自动识别以及对已知话题的动态跟踪。自1997年以来连续举行的多次大规模评测使得话题识别与跟踪研究正逐步成为近来自然语言处理尤其是信息检索领域的一个研究热点,目前国内在这方面的研究尚处在起步阶段。该文介绍了话题识别与跟踪研究的发展历史、研究任务、主要技术及评价方法等,希望能引起相关研究者对这项研究的关注。

This paper describes research into the traditional IR technique to build effective Topic Tracking systems and topic tendency classification based on HowNet. Topic tracking involves tracking a given news event in a stream of news stories i.e. finding all subsequent stories in the news stream that discuss the given event. This research has grown out of the Topic Detection and Tracking (TDT) initiative sponsored by DARPA. Paper focuses on the point of topic and discusses...

This paper describes research into the traditional IR technique to build effective Topic Tracking systems and topic tendency classification based on HowNet. Topic tracking involves tracking a given news event in a stream of news stories i.e. finding all subsequent stories in the news stream that discuss the given event. This research has grown out of the Topic Detection and Tracking (TDT) initiative sponsored by DARPA. Paper focuses on the point of topic and discusses the methods of weight adjustment, event frame and story expansion to improve the tracking effectiveness. Finally paper discusses classification of story tendency based on affective words and event role frame in HowNet. It has been verified by our experiments.

本文研究了如何基于信息检索技术和“知网”实现有效的话题跟踪和话题立场分类。话题跟踪任务就是给出话题相关的训练新闻报道,系统在后续报道中发现与这个话题相关的报道。它属于话题检测与跟踪的一项子任务。本文针对跟踪任务中话题本身的特点,论述了权重调整、事件框架和报道扩充等多种提高跟踪性能的策略,同时基于“知网”中的情感体系和动态角色框架,提出了如何填充框架并结合建立的立场概念库对报道进行话题立场分类。实验证明这些方法是有效的。

Topic Detection and Tracking is a research driven by evaluation,which intends to organize and utilize information stream of texts according to event.Since being brought forward in 1996,it comes under more and more attention.This paper proposes an algorithm of division and multi-level clustering with multi-strategy optimization,which bases on study of today's mature algorithms.The core thought of the algorithm is to divide all data into groups(each group has intrinsic relevance),and cluster in each group...

Topic Detection and Tracking is a research driven by evaluation,which intends to organize and utilize information stream of texts according to event.Since being brought forward in 1996,it comes under more and more attention.This paper proposes an algorithm of division and multi-level clustering with multi-strategy optimization,which bases on study of today's mature algorithms.The core thought of the algorithm is to divide all data into groups(each group has intrinsic relevance),and cluster in each group to produce micro-clusters,and then cluster on all micro-clusters to result in final topics.During the process,various strategies are employed to improve the effect of clustering.The system implemented with the algorithm has been tested on TDT4 corpus.The test indicates the algorithm is one present best algorithm.

话题发现与跟踪是一项评测驱动的研究,旨在依据事件对语言文本信息流进行组织利用。自1996年提出以来,该研究得到了越来越广泛的关注。本文在研究已有成熟算法的基础上,提出了基于分治多层聚类的话题发现算法,其核心思想是把全部数据分割成具有一定相关性的分组,对各个分组分别进行聚类,得到各个分组内部的话题(微类),然后对所有的微类再进行聚类,得到最终的话题,在聚类的过程中采用多种策略进行优化,以保证聚类的效果。基于该算法的系统在TDT4中文语料上进行了测试,结果表明该算法属于目前结果最好的算法之一。

 
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