In this paper we present the inception of Integrated Knowledge Management (IKM). Knowledge management is entering its new stage, after the delays of its “definitionless”, IT-based period, when knowledge got confused with information, losing thus two decades of fruitful development. Although there now is a significant information overload, killing productivity, creativity and innovation, there c...

In the teaching of foreign languages, after all attempts and reforms, understanding has been increasingly strengthened that without reliable linguistic knowledge it is impossible to achieve strong communication skills, which were considered goal grammatical skills play an important role in development language skills. The grammar languages ambiguous. Grammar are equally for speaking, writing, r...

We present the WELTMODELL, a commonsense knowledge base that was automatically generated from aggregated dependency parse fragments gathered from over 3.5 million English language books. We leverage the magnitude and diversity of this dataset to arrive at close to ten million distinct N-ary commonsense facts using techniques from open-domain Information Extraction (IE). Furthermore, we compute ...

The role of grammar in L1 teaching has been a topic long-lasting debate. Czech language instruction is no exception. Based on an almost 200-year-old tradition, the prevailing model grammar- and knowledge-based. Innovations so far have focused mostly general parameters communication interaction class, instead focusing content its didactic transformation. study demonstrates necessity content-focu...

Constructing a natural language dictionary and/or a grammar for computational use is a farreaching project, requiring very important human and material resources. Generalisation of the lexical approaches in natural language modelling confers an essential role to the dictionary in every system for automatic natural language processing. More and more information, which was traditionally encoded b...

We present a framework that couples the syntax and semantics of natural language sentences in a generative model, in order to develop a semantic parser that jointly infers the syntactic, morphological, and semantic representations of a given sentence under the guidance of background knowledge. To generate a sentence in our framework, a semantic statement is first sampled from a prior, such as f...

In recent years, whole cell modeling approaches, which combine existing knowledge and machine learning results, have received considerable attention. These approaches are potentially very efficient for simulating and analyzing physiological function of cells. In this work, entity grammar system is proposed as formalism for knowledge representation and multistratgy learning techniques in systems...

Naturalistic theories of language acquisition assume learners to be endowed with some innate language knowledge. The purpose of this innate knowledge is to facilitate language acquisition by constraining a learner’s hypothesis space. This paper discusses a naturalistic learning system (a Categorial Grammar Learner (CGL)) that differs from previous learners (such as the Triggering Learning Algor...

The present study investigated comparatively the impact of two types of input enhancement (i.e. textual vs. compound enhancement) on developing grammar ability in Iranian EFL setting. Sixty-five female secondary high school students were selected as a homogenous sample out of about a 100-member population based on Nelson language proficiency test. Then, their grammar ability was measured based ...

-A top-down approach to the determination of grammar engineering methods for the construction of Natural Language Grammars for Question Answering Systems based on Intelligent Text Mining for Biomedical applications is presented in the present paper. Our proposal is to start with the formulation of the ultimate task goal such as specialized question answering and derive from it the specification...