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Citation Proximity Analysis (CPA) : A New Approach for Identifying Related Work Based on Co-Citation Analysis
TLDR
The approach called Citation Proximity Analysis (CPA) is a further development of co-citation analysis, but in addition, considers the proximity of citations to each other within an article’s full-text. Expand
Google Scholar's ranking algorithm: The impact of citation counts (An empirical study)
  • J. Beel, Bela Gipp
  • Computer Science
  • Third International Conference on Research…
  • 22 April 2009
TLDR
Citation counts is the highest weighed factor in Google Scholar's ranking algorithm, and Google Scholar seems to be more suitable for searching standard literature than for gems or articles by authors advancing a view different from the mainstream. Expand
Academic Search Engine Optimization ( ASEO ): Optimizing Scholarly Literature for Google Scholar & Co.
This article introduces and discusses the concept of academic search engine optimization (ASEO). Based on three recently conducted studies, guidelines are provided on how to optimize scholarlyExpand
Towards reproducibility in recommender-systems research
TLDR
The recommender-system community needs to survey other research fields and learn from them, find a common understanding of reproducibility, identify and understand the determinants that affect reproduCibility, conduct more comprehensive experiments, and establish best-practice guidelines for recommender -systems research. Expand
Academic Search Engine Optimization (ASEO ): Optimizing Scholarly Literature for Google Scholar & Co.
introduction Researchers should have an interest in ensuring that their articles are indexed by academic search engines such as Google Scholar, IEEE Xplore, PubMed, and SciPlore.org, which greatlyExpand
An exploratory analysis of mind maps
TLDR
An exploratory study of 19,379 mind maps created by 11,179 users from the mind mapping applications 'Docear' and 'MindMeister' to find out how mind maps are structured and which information they contain. Expand
Machine Learning vs. Rules and Out-of-the-Box vs. Retrained: An Evaluation of Open-Source Bibliographic Reference and Citation Parsers
TLDR
This study applies, evaluates and compares ten reference parsing tools in a specific business use case, and confirms that tuning the models to the task-specific data results in the increase in the quality. Expand
Scienstein : A Research Paper Recommender System
TLDR
Scienstein improves the approach of the usually used keyword-based search by combining it with citation analysis, author analysis, source analysis, implicit ratings, explicit ratings and in addition, innovative and yet unused methods like the ‘Distance Similarity Index’ (DSI) and the “In-text Impact Factor” (ItIF). Expand
Google Scholar’s Ranking Algorithm : An Introductory Overview
TLDR
The first steps to reverse-engineering Google Scholar’s ranking algorithm are performed and the results may help authors to optimize their articles for Google Scholar and enable researchers to estimate the usefulness of Google Scholar with respect to their search intention and hence the need to use further academic search engines or databases. Expand
Evaluation of header metadata extraction approaches and tools for scientific PDF documents
TLDR
In the evaluation using papers from the arXiv collection, GROBID delivered the best results, followed by Mendeley Desktop, and SciPlore Xtract, PDFMeat, and SVMHeaderParse also delivered good results depending on the metadata type to be extracted. Expand
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