We participate in the two event extraction tasks of BioNLP 2016 Shared Task: binary relation extraction of SeeDev task and localization relations extraction of Bacteria Biotope task. Convolutional neural network (CNN) is employed to model the sentences by convolution and maxpooling operation from raw input with word embedding. Then, full connected neural network is used to learn senior and sign...

An academic conference typically span a wide range of topics which changes with time. It is known that topics of conferences in different areas may overlap. Constantly, researchers are interested in the trend of a conference like, what the most popular topic/method/problem in this year’s papers is. The relevance of two different conferences reflects such a change as it is an indicator of interd...

Document layout analysis is crucial for understanding document structures. On this task, vision and semantics of documents, relations between components contribute to the process. Though many works have been proposed exploit above information, they show unsatisfactory results. NLP-based methods model as a sequence labeling task insufficient capabilities in modeling. CV-based detection or segmen...

In this paper a steganalysis technique is proposed for pixel value differencing method. This steganographic method, which is immune against conventional attacks, performs the embedding in the difference of the values of pixel pairs. Therefore, the histogram of the differences of an embedded image is different as compared with a cover image. A number of characteristics are identified in the diff...

Word embedding aims to learn a continuous representation for each word. It attracts increasing attention due to its effectiveness in various tasks such as named entity recognition and language modeling. Most existing word embedding results are generally trained on one individual data source such as news pages or Wikipedia articles. However, when we apply them to other tasks such as web search, ...

In this paper, a wavelet based watermarking scheme for the protection of document and graphics images is proposed. Document and graphics images are different from other images as such images are typically in two colors only (generally white as background and black or other color as text or drawing). In document or graphics images, white background area is usually more than the text or drawing c...

The problem of code generation from textual program descriptions has long been viewed as a grand challenge in software engineering. In recent years, many deep learning based approaches have proposed, which can generate sequence description. However, the existing ignore global relationships among API methods, are important for understanding usage APIs. this paper, we propose to model dependencie...

With the booming of Internet Things (IoT) and speedy advancement Location-Based Social Networks (LBSNs), Point-Of-Interest (POI) recommendation has become a vital strategy for supporting people's ability to mine their POIs. However, classical models, such as collaborative filtering, are not effective structuring POI recommendations due sparseness user check-ins. Furthermore, LBSN distinct from ...

Neural embeddings have been used with great success in Natural Language Processing (NLP). They provide compact representations that encapsulate word similarity and attain state-of-the-art performance in a range of linguistic tasks. The success of neural embeddings has prompted significant amounts of research into applications in domains other than language. One such domain is graph-structured d...

Neural Architecture Search (NAS) automates and prospers the design of neural networks. Estimator-based NAS has been proposed recently to model relationship between architectures their performance enable scalable flexible search. However, existing estimator-based methods encode architecture into a latent space without considering graph similarity. Ignoring similarity in node-based search may ind...