In today’s digital world securing different forms of content is very important in terms of protecting copyright and verifying authenticity. One example is watermarking of digital audio and images. We believe that a marking scheme analogous to digital watermarking but for documents is very important. In this paper we describe the use of laser amplitude modulation in electrophotographic printers ...

One of the most significant graph data analysis tasks is classification, as graphs are complex structures used for illustrating relationships between entity pairs. Graphs essential in many domains, such description chemical molecules, biological networks, social relationships, etc. Real-world complicated and large. As a result, there need to find way represent or encode graph’s structure so tha...

Machine translation quality estimation is a challenging task in the WMT evaluation campaign. Feature extraction plays an important role in automatic quality estimation, and in this paper, we propose neural network features, including embedding features and cross-entropy features of source sentences and machine translations, to improve machine translation quality estimation. The sentence embeddi...

In the last several years, neural network models have significantly improved accuracy in a number of NLP tasks. However, one serious drawback that has impeded their adoption in production systems is the slow runtime speed of neural network models compared to alternate models, such as maximum entropy classifiers. In Devlin et al. (2014), the authors presented a simple technique for speeding up f...

According to the website AcronymFinder.com which is one of the world's largest and most comprehensive dictionaries of acronyms, an average of 37 new human-edited acronym definitions are added every day. There are 379,918 acronyms with 4,766,899 definitions on that site up to now, and each acronym has 12.5 definitions on average. It is a very important research topic to identify what exactly an ...

This paper discuss natural language watermarking, which analyzes patterns inside sentences of a given natural language text document, in order to embed individual watermark messages. The term ”natural language watermarking” stands for the process of the embedding of watermark messages into a text document, using natural language components as the carrier, in such a way that the modifications ar...

In today’s digital world securing different forms of content is very important in terms of protecting copyright and verifying authenticity. One example is watermarking of digital audio and images. We believe that a marking scheme analogous to digital watermarking but for documents is very important. In this paper we describe the use of laser amplitude modulation in electrophotographic printers ...

Many facts change over time, which is a fundamental aspect of our physical environment. In the case pandemic articles, user not interested in creation date document, but and cause last pandemic. Fake news can be better combated by having document with temporal focus. Currently, neither sequence events nor focus considered when obtaining documents. Despite limited number aspects available datase...

Locally linear embedding is an effective nonlinear dimensionality reduction method for exploring the intrinsic characteristics of high dimensional data. This paper proposes a new manifold learning method, which is based on locally linear embedding and growing neural gas and is termed growing locally linear embedding (GLLE). GLLE overcomes the major limitations of the original locally linear emb...

In this paper, we explore the usage of Word Embedding semantic resources for Information Retrieval (IR) task. This embedding, produced by a shallow neural network, have been shown to catch semantic similarities between words (Mikolov et al., 2013). Hence, our goal is to enhance IR Language Models by addressing the term mismatch problem. To do so, we applied the model presented in the paper Inte...