Relation classification is an important semantic processing task in the field of natural language processing (NLP). In this paper, we present a novel model BRCNN to classify the relation of two entities in a sentence. Some state-of-the-art systems concentrate on modeling the shortest dependency path (SDP) between two entities leveraging convolutional or recurrent neural networks. We further exp...

one of the most important issues always facing banks and financial institutes is the issue of credit risk or the possibility of failure in the fulfillment of obligations by applicants who are receiving credit facilities. the considerable number of banks’ delayed loan payments all around the world shows the importance of this issue and the necessary consideration of this topic. accordingly, many...

in the past, mining activities have generated major acid drainage sources, which usually carry dissolved metals that flow into the main rivers of the affected basins. the study looks at natural attenuation processes in local, sub-basin and basin areas, in the el bierzo and odiel basins of spain, where coal and metal mining activities were formerly conducted. in this study, sampling and in situ ...

tehran is one of the most polluted metropolises in the world. sink capacity for absorption and assimilation of pollution is reduced generally due to failure in inclusion of ecological aspects in regional land use development planning. the present condition of air and water related issues in tehran are greatly affected by landscape structural alterations at urban level. in this research the focu...

Recently, the next-item/basket recommendation system, which considers the sequential relation between bought items, has drawn attention of researchers. The utilization of sequential patterns has boosted performance on several kinds of recommendation tasks. Inspired by natural language processing (NLP) techniques, we propose a novel neural network (NN) based next-song recommender, CNN-rec, in th...

Continuous space word representations extracted from neural network language models have been used effectively for natural language processing, but until recently it was not clear whether the spatial relationships of such representations were interpretable. Mikolov et al. (2013) show that these representations do capture syntactic and semantic regularities. Here, we push the interpretation of c...

This paper investigates several language phenomena either considered deviant by linguistic standards or insufficiently addressed by existing approaches. These include co-occurrence violations, some forms of ellipsis and extraneous forms, and conjunction. Relaxation techniques for their treatment in Natural Language Understanding Systems are discussed. These techniques, developed within the Augm...