Discovering Temporal Relations with TICTAC

نویسنده

  • Georgiana Puşcaşu
چکیده

Temporal information plays an important role in many NLP applications. The identification of temporal relations between temporal entities (events and temporal expressions) is indispensable in obtaining the temporal interpretation of a given text. This paper presents our approach for discovering temporal relations using the temporal annotation system we have developed. This system is called TICTAC (Syntactico-Semantic Temporal Annotation Cluster) and it comprises both knowledge based and statistical techniques. It has achieved the best performance among all systems participating at the TempEval competition organised as part of SemEval-2007, competition that evaluated temporal relation identification capabilities.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

WVALI: Temporal Relation Identification by Syntactico-Semantic Analysis

This paper reports on the participation of University of Wolverhampton and University of Alicante at the SemEval-2007 TempEval evaluation exercise. TempEval consisted of three tasks involving the identification of event-time and event-event temporal relations. We participated in all three tasks with TICTAC (SyntacticoSemantic Temporal Annotation Cluster), a system comprising both knowledge base...

متن کامل

Discovering Temporal Knowledge from a Crisscross of Timed Observations

This paper is concerned with the discovering of temporal knowledge from a sequence of timed observations provided by a system monitoring of dynamic process. The discovering process is based on the Stochastic Approach framework where a series of timed observations is represented with a Markov chain. From this representation, a set of timed sequential binary relations between discrete event class...

متن کامل

Mining Sensor Data in Smart Environment for Temporal Activity Prediction

Technological enhancements aid development and advanced research in smart homes and intelligent environments. The temporal nature of data collected in a smart environment provides us with a better understanding of patterns over time. Prediction using temporal relations is a complex and challenging task. To solve this problem, we suggest a solution using probability based model on temporal relat...

متن کامل

Temporal Pattern Discovery for Anomaly Detection in a Smart Home

The temporal nature of data collected in a smart environment provides us with a better understanding of patterns over time. Detecting anomalies in such datasets is a complex and challenging task. To solve this problem, we suggest a solution using temporal relations. Temporal pattern discovery based on modified Allen’s temporal relations [5] has helped discover interesting patterns and relations...

متن کامل

TimeSleuth: A Tool for Discovering Causal and Temporal Rules

Discovering causal and temporal relations in a system is essential to understanding how it works, and to learning to control the behaviour of the system. TimeSleuth is a causality miner that uses association relations as the basis for the discovery of causal and temporal relations. It does so by introducing time into the observed data. TimeSleuth uses C4.5 as its association discoverer, and by ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2007