In knowledge management systems, ontologies play an important role as a backbone for providing and accessing knowledge sources. They are largely used in the next generation of the Semantic Web that focuses on supporting a better cooperation between humans and ma‐ chines [2]. Since manual ontology construction is costly, time-consuming, error-prone, and inflexible to change, it is hoped that an ...

Semantic similarity is a confidence score that replicates semantic equivalence between the meanings of two sentences. Determining the similarity among sentences is one of the critical tasks which have a wide-ranging impact in recent NLP applications. This paper presents a method for identifying semantic sentence similarity among sentences using semantic relation of word senses across the differ...

Human languages includes many ambiguity words, each word will have different meaning or sense. Identifying correct sense of the word is purely depended on the context in which the word appears. There are many approaches to find the correct sense of the word. Word sense disambiguation is the process of differentiating among senses of words. WSD plays a vital role to reduce the ambiguity about th...

a bilingual corpus is considered as a very important knowledge source and an inevitable requirement for many natural language processing (nlp) applications in which two languages are involved. for some languages such as persian, lack of such resources is much more significant. several applications, including statistical and example-based machine translation needs bilingual corpora, in which lar...

Natural language is most common way to communicate with each other but sometime we can’t understand other languages to understand different languages machine translation is needed. Machine translation is the best application which helps to understand any other language in less cost and less time. In this some problems are faced by researchers: words which pronounce same but having different mea...

We introduce a new task, visual sense disambiguation for verbs: given an image and a verb, assign the correct sense of the verb, i.e., the one that describes the action depicted in the image. Just as textual word sense disambiguation is useful for a wide range of NLP tasks, visual sense disambiguation can be useful for multimodal tasks such as image retrieval, image description, and text illust...

Previously, we had developed the concept of a Segmental Neural Net (SNN) for phonetic modeling in continuous speech recognition (CSR). This kind of neural network technology advanced the state-of-the-art of large-vocabulary CSR, which employs Hidden Marlcov Models (HMM), for the ARPA 1oo0-word Resource Management corpus. More Recently, we started porting the neural net system to a larger, more ...

We propose a novel architecture for natural language inference. On top of a traditional recurrent neural net with attention architecture, we add memory-based modules, residual connections, and richer word embeddings. With these, we are able to achieve 76.6% accuracy.

This paper presents the potential of the herein so-called neural net filters in communication systems. The use of integrated signaling and coding techniques in modern modulation schemes has not a right correspondence in the same digital signal processing integrated tools. The neural net filter seems to be the needed contribution. Introduced from de basic neural structure associated with coding ...