Although deep learning breakthroughs in NLP are based on learning distributed word
representations by neural language models, these methods suffer from a classic drawback …

Over the past decade, analogies, in the form of word-level analogies, have played a
significant role as an intrinsic measure of evaluating the quality of word embedding methods …

It is an object to highly accurately perform semantic relation (21) Appl. No.: 14/423,142 ship
extraction from text data by performing Supervised learning of multiple classes using an …

Given appropriate representations of the semantic relations between carpenter and wood
and between mason and stone (for example, vectors in a vector space model), a suitable …

Work on authorship attribution has traditionally focused on long texts. In this work, we tackle
the question of whether the author of a very short text can be successfully identified. We use …

The availability of large idea repositories (eg, the US patent database) could significantly
accelerate innovation and discovery by providing people with inspiration from solutions to …

Extracting semantic relations among entities is an important first step in various tasks in Web
mining and natural language processing such as information extraction, relation detection …

There have been several efforts to extend distributional semantics beyond individual words,
to measure the similarity of word pairs, phrases, and sentences (briefly, tuples; ordered sets …

Background: Detecting adverse drug reactions (ADRs) is an important task that has direct
implications for the use of that drug. If we can detect previously unknown ADRs as quickly as …

Applying learning techniques to acquire action models is an area of intense research
interest. Most previous work in this area has assumed that there is a significant amount of …