This paper describes our sentiment classification system for microblog-sized documents, and documents where a topic is present. The system consists of a softvoting ensemble of a word2vec language model adapted to classification, a convolutional neural network (CNN), and a longshort term memory network (LSTM). Our main contribution consists of a way to introduce topic information into this model...

Knowledge-aware methods have boosted a range of natural language processing applications over the last decades. With gathered momentum, knowledge recently has been pumped into enormous attention in document summarization, one applications. Previous works reported that knowledge-embedded summarizers excel at generating superior digests, especially terms informativeness, coherence, and fact consi...

Non-negative Matrix Factorization (NMF) and its variants have been successfully used for clustering text documents. However, NMF approaches like other models do not explicitly account the contextual dependencies between words. To remedy this limitation, we draw inspiration from neural word embedding posit that words frequently co-occur within same context (e.g., sentence or document) are likely...

Fingerprint verification is one of the most reliable personal identification methods. With the fast development of the Internet, the usage of e-documents becomes more popular. Nonetheless, the old way of putting fingerprints or stamps on a hardcopy is no longer possible for e-documents. In this paper, a document fingerprinting and de-fingerprinting system is presented. In the document fingerpri...

This document discourages the practice of embedding references to unique, globally-routable IP addresses in Internet hosts, describes some of the resulting problems, and considers selected alternatives. This document is intended to clarify best current practices in this regard.