Topic Hierarchy Generation

This post continues the problem of topic summarization posted earlier. Here I try to collect research articles related to the problem of topic hierarchy generation which is an important step for topic summarization.

1) Non-Parametric Estimation of Topic Hierarchies from Texts with Hierarchical Dirichlet Processes (link). Journal of Machine Learning Research 2011.

2) A Practical Web-based Approach to Generating Topic Hierarchy for Text Segments (link). CIKM 2004.

3) Finding Topic Words for Hierarchical Summarization (link). SIGIR 2001.

4) The Nested Chinese Restaurant Process and Bayesian Non-parametric Inference of Topic Hierarchies (link). Journal of the ACM 2010.

5) Mining bilingual topic hierarchies from unaligned text (link). IJCNLP 2011.

6) Domain-Assisted Product Aspect Hierarchy Generation: Towards Hierarchical Organization of Unstructured Consumer Reviews (link). ACL 2011.

7) (TBA)

(to be updated).

Topic Directory (~590K available categories so far)

http://www.dmoz.org/

The Open Directory Project is the largest, most comprehensive human-edited directory of the Web. It is constructed and maintained by a vast, global community of volunteer editors.

It is in multiple languages. Great!

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Cheers,
Vu

Summarizing contents across websites in the Internet

Summarizing contents across websites in the Internet:

http://www.iresearch-reporter.com/
http://ultimate-research-assistant.com/

The summary quality of the above systems is not actually good (i think). One possible improvement is to focus mainly on summarizing contents from research papers which contain very useful and detailed technical materials. It could be regarded to "Related Work Summarization" (see my paper at here).

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Cheers,
Vu

Topic summarization

Given a scenario in which the system takes the input with a research topic and needs to generate a summary of related works relevant to that topic automatically.
--> I think this research problem is still open and actually very challenging. It requires advanced processing which combines many fields in AI such as: NLP, IR, IE, ...

Some initial works (including mine) as follows:
1) Scientific Paper Summarization Using Citation Summary Networks by Qazvinian V. et al. (COLING 2008).
--> this work only targets single article summarization using a clustering approach based on citation summary networks.
2) Generating surveys of scientific paradigms by Saif Mohammad et al. (NAACL 2009).
--> this work explores the usefulness of citation summary in compared to summary from abstracts or full text of articles.
3) Towards Automated Related Work Summarization by Cong Duy Vu HOANG et al. (COLING 2010)
--> this work does not use citation summary but tries to take advantage of full text of article in generating related work summary.
It makes a strong assumption that each related work summary follows a topic hierarchy tree which is provided as the input of summarization system. The system then proposes two different strategies (general & specific content summarization) based on manual rhetorical analysis on how humans use topic hierarchy tree to generate related work summary.
4) Identifying Non-Explicit Citing Sentences for Citation-Based Summarization by Vahed Qazvinian and Dragomir R. Radev (ACL 2010)
--> TBA
5) Context Identification of Sentences in Related Work Sections using a Conditional Random Field: Towards Intelligent Digital Libraries by Angrosh M. A. et al. (JCDL 2010)
6) Imitating Human Literature Review Writing: An Approach to Multi-document Summarization by Jaidka K. et al. (ICADL 2010)
7) Analysis of the Macro-Level Discourse Structure of Literature Reviews by Jaidka K. et al. (Online Information Review)
8) Ultimate Research Assistant: http://ultimate-research-assistant.com/
9) iResearch Reporter: http://iresearch-reporter.com//
10) TBA

Future works (what I come up in my mind now) includes:
- Given a research topic --> automatically generate a topic hierarchy tree of that topic.
- A systematic comparison of summaries built from citations, abstracts, full text of articles. Which ones are more useful to users?
- An initial add-in component integrated into online ACL anthology system.
- Some other issues improve the summarization performance (i.e. use rhetorical discourse analysis, ...)
- ...
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Cheers,
Vu