کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
515526 867038 2013 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Ambiguous author query detection using crowdsourced digital library annotations
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
پیش نمایش صفحه اول مقاله
Ambiguous author query detection using crowdsourced digital library annotations
چکیده انگلیسی

The name ambiguity problem is especially challenging in the field of bibliographic digital libraries. The problem is amplified when names are collected from heterogeneous sources. This is the case in the Scholarometer system, which performs bibliometric analysis by cross-correlating author names in user queries with those retrieved from digital libraries. The uncontrolled nature of user-generated annotations is very valuable, but creates the need to detect ambiguous names. Our goal is to detect ambiguous names at query time by mining digital library annotation data, thereby decreasing noise in the bibliometric analysis. We explore three kinds of heuristic features based on citations, metadata, and crowdsourced topics in a supervised learning framework. The proposed approach achieves almost 80% accuracy. Finally, we compare the performance of ambiguous author detection in Scholarometer using Google Scholar against a baseline based on Microsoft Academic Search.


► We detect ambiguous names at query time by mining digital library annotation data.
► Three kinds of features based on citations, metadata, and crowdsourced topics are explored.
► The proposed approach achieves almost 80% accuracy.
► Our approach outperforms a baseline derived from Microsoft Academic Search.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Information Processing & Management - Volume 49, Issue 2, March 2013, Pages 454–464
نویسندگان
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