Learn More
This paper presents an approach for identifying similar documents that can be used to assist scientists in finding related work. 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. The underlying idea is(More)
In this demonstration-paper we introduce Docear, an 'academic literature suite'. Docear offers to scientists what an office suite like Microsoft Office offers to office workers. While an office suite bundles various applications for office workers (word processing, spreadsheets, presentation software, etc.), Docear bundles several applications for(More)
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 scholarly literature for academic search engines in general and for Google Scholar in particular. In addition, we briefly discuss the risk of researchers' illegitimately(More)
Plagiarism Detection Systems have been developed to locate instances of plagiarism e.g. within scientific papers. Studies have shown that the existing approaches deliver reasonable results in identifying copy&paste plagiarism, but fail to detect more sophisticated forms such as paraphrased plagiarism, translation plagiarism or idea plagiarism. The(More)
Mind maps are used by millions of people. In this paper we present how information retrieval on mind maps could be used to enhance expert search, document summarization, keyword based search engines, document recommender systems and determining word relatedness. For instance, words in a mind map could be used for creating a skill profile of the mind maps'(More)
In a previous paper we provided guidelines for scholars on optimizing research articles for academic search engines such as Google Scholar. Feedback in the academic community to these guidelines was diverse. Some were concerned researchers could use our guidelines to manipulate rankings of scientific articles and promote what we call 'academic search engine(More)
Google Scholar is one of the major academic search engines but its ranking algorithm for academic articles is unknown. In a recent study we partly reverse-engineered the algorithm. This paper presents the results of our second study. While the previous study provided a broad overview, the current study focused on analyzing the correlation of an article's(More)
Over 80 approaches for academic literature recommendation exist today. The approaches were introduced and evaluated in more than 170 research articles, as well as patents, presentations and blogs. We reviewed these approaches and found most evaluations to contain major shortcomings. Of the approaches proposed, 21% were not evaluated. Among the evaluated(More)
Offline evaluations are the most common evaluation method for research paper recommender systems. However, no thorough discussion on the appropriateness of offline evaluations has taken place, despite some voiced criticism. We conducted a study in which we evaluated various recommendation approaches with both offline and online evaluations. We found that(More)