1,367 research outputs found
AntiPlag: Plagiarism Detection on Electronic Submissions of Text Based Assignments
Plagiarism is one of the growing issues in academia and is always a concern
in Universities and other academic institutions. The situation is becoming even
worse with the availability of ample resources on the web. This paper focuses
on creating an effective and fast tool for plagiarism detection for text based
electronic assignments. Our plagiarism detection tool named AntiPlag is
developed using the tri-gram sequence matching technique. Three sets of text
based assignments were tested by AntiPlag and the results were compared against
an existing commercial plagiarism detection tool. AntiPlag showed better
results in terms of false positives compared to the commercial tool due to the
pre-processing steps performed in AntiPlag. In addition, to improve the
detection latency, AntiPlag applies a data clustering technique making it four
times faster than the commercial tool considered. AntiPlag could be used to
isolate plagiarized text based assignments from non-plagiarised assignments
easily. Therefore, we present AntiPlag, a fast and effective tool for
plagiarism detection on text based electronic assignments
Learning semantic sentence representations from visually grounded language without lexical knowledge
Current approaches to learning semantic representations of sentences often
use prior word-level knowledge. The current study aims to leverage visual
information in order to capture sentence level semantics without the need for
word embeddings. We use a multimodal sentence encoder trained on a corpus of
images with matching text captions to produce visually grounded sentence
embeddings. Deep Neural Networks are trained to map the two modalities to a
common embedding space such that for an image the corresponding caption can be
retrieved and vice versa. We show that our model achieves results comparable to
the current state-of-the-art on two popular image-caption retrieval benchmark
data sets: MSCOCO and Flickr8k. We evaluate the semantic content of the
resulting sentence embeddings using the data from the Semantic Textual
Similarity benchmark task and show that the multimodal embeddings correlate
well with human semantic similarity judgements. The system achieves
state-of-the-art results on several of these benchmarks, which shows that a
system trained solely on multimodal data, without assuming any word
representations, is able to capture sentence level semantics. Importantly, this
result shows that we do not need prior knowledge of lexical level semantics in
order to model sentence level semantics. These findings demonstrate the
importance of visual information in semantics
Academic integrity at the University of Montenegro : pathway to certification
Academic dishonesty is one of the major challenges in higher education. In developed countries, higher education institutions have, for some years now, begun to put in place strategies and mechanisms to combat academic misconduct. In developing countries, such as Montenegro, the formalisation of processes to strengthen academic integrity is a relatively new concern. In this paper, we will analyse the framework for the development of a determined academic integrity strategy, which resulted in the international certification of the University of Montenegro. Based on the literature review on academic integrity and using the case analysis method, we highlight the steps in the certification process. We will show how the holistic approach that has been adopted strengthens the culture of academic integrity
Impact Factor: outdated artefact or stepping-stone to journal certification?
A review of Garfield's journal impact factor and its specific implementation
as the Thomson Reuters Impact Factor reveals several weaknesses in this
commonly-used indicator of journal standing. Key limitations include the
mismatch between citing and cited documents, the deceptive display of three
decimals that belies the real precision, and the absence of confidence
intervals. These are minor issues that are easily amended and should be
corrected, but more substantive improvements are needed. There are indications
that the scientific community seeks and needs better certification of journal
procedures to improve the quality of published science. Comprehensive
certification of editorial and review procedures could help ensure adequate
procedures to detect duplicate and fraudulent submissions.Comment: 25 pages, 12 figures, 6 table
Text-matching software in post-secondary contexts: A systematic review protocol
This protocol outlines the methods for our systematic review on commercial text-matching software (TMS). We propose to use Joanna Briggs Instituteâs (JBI) Methodology for Mixed Methods Systematic Reviews. This systematic review will provide insights into how TMS is used in post-secondary contexts, highlighting evidence relating to how well such software reduces incidences of plagiarism, and also how it can be used for educational purposes to support student learning at the undergraduate and graduate levels
The benefits from publicly funded research
Research, Technological change, Government Policy
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