Full Seminar Details

Anita Khadka

 Anita Khadka
Can we do better than Co-Citations? Bringing Citation Proximity Analysis from idea to practice in research paper recommendation
This event took place on Wednesday 11 October 2017 at 11:30


Scholarly publications are increasing exponentially every year, creating challenges for researchers to stay in touch with new relevant articles in their domain. Recommender Systems can serve dual purpose. To researchers, it can help them to stay in touch with the latest developments in their field. To authors, it can broaden their audiences resulting in increased number of reads and therefore more effective dissemination of knowledge. Citation Proximity Analysis (CPA) is based on the Co-Citation approach and the underlying heuristic of CPA is that the closer the documents are cited together the more likely they are related. In this work, a step by step scalable approach is developed for building CPA-based recommender systems. In this approach, three new novel proximity functions are introduced, extending the basic assumption of Co-Citation analysis to take the distance between the cocited documents into account. A CPA based recommender system was built from a corpus of more than 350,000 full-texts articles and a user survey was conducted to perform an initial evaluation. And, two of our three proximity functions used within CPA outperformed CoCitation based baseline approach by 25%.

Watch the webcast replay >>

View all past events

 
Maven of the month logo - Photo of Prof. Ricardo Baeza-Yates

Maven of the Month

We are also inviting top experts in AI and Knowledge Technologies to discuss major socio-technological topics with an audience that comprises both members of the Knowledge Media Institute, as well as the wider staff at The Open University. Differently from our seminar series, these events follow a Q&A format.

Past events

CONTACT US

Knowledge Media Institute
The Open University
Walton Hall
Milton Keynes
MK7 6AA
United Kingdom

Tel: +44 (0)1908 653800

Fax: +44 (0)1908 653169

Email: KMi Support

COMMENT

If you have any comments, suggestions or general feedback regarding our website, please email us at the address below.

Email: KMi Development Team