Extraction of Temporal Expressions from Finnish News-feed

Extra tion of Temporal Expressions from Finnish News-feed

Applying Semantic Classes in Event Detection and Tracking

Event detection and tracking is a somewhat recent area of information retrieval research. The detection is about spotting new, previously unreported real-life events from online news-feed, while the tracking assigns documents to previously spotted events. We propose a new vector model consisting of four semantic classes from the documents: locations, proper names, temporal expressions and norma...

Utilizing Temporal Information in Topic Detection and Tracking

The harnessing of time-related information from text for the use of information retrieval requires a leap from the surface forms of the expressions to a formalized time-axis. Often the expressions are used to form chronological sequences of events. However, we want to be able to determine the temporal similarity, i.e., the overlap of temporal references of two documents and use this similarity ...

Automatic Temporal Expression Normalization with Reference Time Dynamic-Choosing

Temporal expressions in texts contain significant temporal information. Understanding temporal information is very useful in many NLP applications, such as information extraction, documents summarization and question answering. Therefore, the temporal expression normalization which is used for transforming temporal expressions to temporal information has absorbed many researchers’ attentions. B...

FSS-TimEx for TempEval-3: Extracting Temporal Information from Text

We describe FSS-TimEx, a module for the recognition and normalization of temporal expressions we submitted to Task A and B of the TempEval-3 challenge. FSS-TimEx was developed as part of a multilingual event extraction system, Nexus, which runs on top of the EMM news processing engine. It consists of finite-state rule cascades, using minimalistic text processing stages and simple heuristics to ...