Chowdary2009 USUM: Update Summary Generation System

 C. Ravindranath Chowdary and P. Sreenivasa Kumar, "USUM: Update Summary Generation System", In Advances in Computational Linguistics. Research in Computing Science Vol. 41, 2009, pp. 229-240.

Paper ID (BibTexKey)    : Chowdary2009
Paper category               : (main reference)
Abstract keyphrases       :
query-based, extractive, multi-documen, and updated summarization

scenario where the source documents are not accessible

embed the sentences of the current summary into the new document and then perform query specific
summary generation on that document. 

performance..good ..quality and efficiency.
graph-based page-rank approach 

1.    INTRODUCTION
a.    Paper type (no survey)
b.    Something new/novel (e.g. algorithm, method, technique, approach)? (Y)
Problem: given an extractive summary that is generated for a given query on a set of documents, upon the arrival of a new document, the summary has to be updated without considering the initial
set of documents.  This problem is not addressed in the literature.

c.     Paper readability/understandability? (easy)

d.    Interesting material? (Very)
e.    Detail enough? (Y)
f.    Google Scholar citation count: counting mount, date of publication: 0, 10/4/2010, Feb 2009
g.    Publisher tier: NA
h.    Summarization category: graph-based

2.    CONTENT
a.    Background
Often the information pertaining to a topic is present across several web pages.It will be of great help for the user if a query specific multidocument summary is generated.
In multi-document summary generation, other issues like time, ordering of extracted sentences, scalability etc. will arise.

b.    Description in brief the core content, something new proposed by the authors 

Generating Summary-Embedded Document
We ..  graph based approach .. update summarization.
sentence .. node and edges .. similarity score between them.

Algorithm 1 sketches the details of the embedding of the current summary into the new document

Similarity (calculated using Equation 1)

Update Summary Generation
Summary generation on the embedded document is discussed.
Score of the node is calculated based on the query posed by the user i.e., the node gets score based on its relevance to the query.

Node score calculation is based on the Equation 2.
The sentences in the summary generated using Algorithm 2 are rearranged in the document order.
This summary is complete, coherent and also non-redundant.

Experimental Setup
Initial summary .. using the MEAD (for the first 15 of the 25 documents)16th document will be the new document into which the summary is to be embedded.
The summary is generated for the given query on the embedded document and this generated summary will be embedded into 17th document. The process is repeated till the summary on the last embedded document(25th) is generated.


c.    Machine Learning/Text Mining technique used. NO

d.    Corpus used  DUC 2006

e.    NL knowledge used: NO

f.    Evaluation metric used ROUGE

g.    Performance, and how it compares with others
ROUGE-1 0.38980
ROUGE-2 0.08179
ROUGE-W 0.09429
ROUGE-SU4 0.13757
No comparison with other methods
h.    The strength and weakness of core content (according to authors)
Complete, Coherent, Quality Summary, Efficient

i.    Future works: NA


3 COMMENTS
Bagaimana kalau data baru tidak sama dengan yang lama untuk informasi/hal yang sama?