KDD

KDD Cup 2013 challenged participants to tackle the problem of author name ambiguity in a digital library of scientific publications. The competition consisted of two tracks, which were based on large-scale datasets from a snapshot of Microsoft Academic ...

The track 1 problem in KDD Cup 2013 is to discriminate between papers confirmed by the given authors from the other deleted papers. This paper describes the winning solution of team National Taiwan University for track 1 of KDD Cup 2013. First, we ...

This paper describes our submission to the KDD Cup 2013 Track 1 Challenge: Author-Paper Indentification in the Microsoft Academic Search database. Our approach is based on Gradient Boosting Machine (GBM) of Friedman ([5]) and deep feature engineering. ...

This paper describes team mb74's solution to Track 1 of KDD Cup 2013. The challenge is to determine whether an author has written a given paper in the Microsoft Academic Search database. The key part of our solution is the feature generation which is ...

The ability to search literature and collect/aggregate metrics around publications is a central tool for modern research. Both academic and industry researchers across hundreds of scientific disciplines, from astronomy to zoology, increasingly rely on ...

We present the ideas and methodologies that we used to address the KDD Cup 2013 challenge on author-paper identification. We firstly formulate the problem as a personalized ranking task and then propose to solve the task through a supervised learning ...

Track 2 in KDD Cup 2013 aims at determining duplicated authors in a data set from Microsoft Academic Search. This type of problems appears in many large-scale applications that compile information from different sources. This paper describes our ...

Author name ambiguity is a frequently encountered problem in digital publication libraries such as Microsoft Academic Search. The cause of this problem mostly is that different authors may publish under the same name, while the same author could publish ...

This paper describes our team's (BS Man & Dmitry & Leustagos) approach to the KDD Cup 2013 track 2 challenge: Author Disambiguation in the Microsoft Academic Search database.

Name disambiguation, which aims to identify multiple names which correspond to one person and same names which refer to different persons, is one of the most important basic problems in many areas such as natural language processing, information ...