This document discusses techniques for temporal and event tagging to analyze documents and extract events and their temporal relationships. It proposes applying summarization as a way to filter sentences and events. The approach uses three components: prior ranking of sentences, cosine similarity ranking, and a PageRank-like algorithm. It evaluates the approach on DUC2007 data and finds it significantly reduces the number of extracted events while maintaining sentence selection quality. However, the document also notes limitations in existing technology for temporal analysis across multiple documents.

1. TIMELINE FROM
NEWS
KK Lo

2. GOAL...

4. RELATED
WORK

5. Topic Detection and
Tracking
2 communities
Temporal and Event
Tagging

6. Events of interest
discovering
new topic
classifying
documents
? tracking topics
Topic Detection and Tracking

7. publication date =event happen time?
Problems
assume each article is an event
lack of details

8. ?
Tagging events and
their temporal
relationships
Temporal and Event Tagging

9. Problems
Event
Event
Event
Event
Event
Event
Result obtained from the TARSQI toolkit
Event
too many Events....

10. MY SOLUTION

11. APPLY
SUMMARIZATION
TECHNIQUE AS
EVENT FILTERING

12. 3 components

13. prior probability
Prior Ranking
0
1. Sentence A
2. Sentence B
3. Sentence C
4. ...
Beginning sentence has a higher
prior probability

14. cosine similarities
s1
Grasshopper
s2
s3
s4
s5
A Page-rank-like ranking
algorithm

15. explicit time
event instance
event-event link
event-time link
TARSQI Toolkit
From
TEXT to
TimeML

16. Events in TimeML
Event Filtering
Appear in the NO
Top Selected BYE
Sentences?
YES
PICK

17. 2008Dec
Temporal
event2 event1
Reasoner
event3
2009
Find the (start, end) bound for
each events

18. RESULT?

19. Sentence Selection Quality
Special 250-words summary form 25 documents with
DUC2007 Data Set
Thanks to
for the data and ROUGE =p

20. Effect of Sentence Filtering
choosing the top 10 sentences
D0701A D0720E
#Event before
3320 1435
Filtering
#Event after
67 37
Filtering
How can we represent 3320 events
on a timeline?

21. Time-Event Anchoring
D0701A D0720E
#Event before
3320 1435
Filtering
#Failure 3085 1129
#Event after 67 37
Filtering
#Failure 49 29
This shows that my approach is a failure

22. TARSQI only support
single document
WHY?
e.g. 50 tagged events, Unable to deduce the
only 50 pairs of relationships for all pair
relation are tagged of events
should be 50C2 = 1225

23. LESSON
LEARNED

24. Temporal and Event
Tagging 3 areas
my project
Automatic
Summarization
Topic Detection
and Tracking

25. The limit of existing
technology
OR EVEN
The limit of temporal
analysis
cannot get enough information from the documents

26. cosine similarity with tf-idf
weighting is computational
expensive
2.5 hrs for 867 sentences

27. DUC2007 Documents are
hard to parse
different documents have different
format........
no standard date format...
contains some special
characters that cause troubles
to XML parsers...

28. Q&A