We propose a range of deep lexical acquisition methods which make use of morphological, syntactic and ontological language resources to model word similarity and bootstrap from a seed lexicon. The different methods are deployed in learning lexical items for a precision grammar, and shown to each have strengths and weaknesses over different word classes. A particular focus of this paper is the r...

Many natural language processing tasks make use of a lexicon – typically the words collected from some annotated training data along with their associated properties. We demonstrate here the utility of corpora-independent lexicons derived from machine readable dictionaries. Lexical information is encoded in the form of features in a Conditional Random Field tagger providing improved performance...

We are most grateful for the comments made by Earl (2014) on our paper, Frey and Gallus (2014). In particular, we are pleased that we can fully agree on the fundamental point we wanted to make: decisions by individuals (as well as by organizational units) do not map directly and in an unchanged way to the macro level. Rather, the aggregation process linking the microand the macro-level must be ...

In 1937, Ronald Coase argued that firms will exist only in environments in which firms perform better than markets could. To create space for firms, Coase suggested that some environments might be plagued by “transaction costs” that cause markets to perform poorly. Coase’s paper was to become the cornerstone of the economic theory of the firm (i.e., the “make or buy” decision: which activities ...

This paper proposes and evaluates a model of supply chains as networks of auctions. In this model, companies are represented according to the first level of the Supply Chain Council’s SCOR model and the trading strategy of the agents is adapted from a model proposed by Steiglitz and colleagues. Specifically, the highest level of SCOR treats a company as comprising three functions, namely Source...

cancer registration is an important source for measuring the burden of cancer in a population. in practice, however, quite frequently incorrect patients are registered or data items can be inaccurately recorded or not recorded at all. also the process or quality of these registrations varies among countries. in this paper, we briefly discussed some statistical techniques including; mortality an...

Lexical knowledge influences how human listeners make decisions about speech sounds. Positive lexical effects (faster responses to target sounds in words than in nonwords) are robust across several laboratory tasks, while negative effects (slower responses to targets in more word-like nonwords than in less word-like nonwords) have been found in phonetic decision tasks but not phoneme monitoring...

Current Arabic lexicons, whether computational or otherwise, make no distinction between entries from Modern Standard Arabic (MSA) and Classical Arabic (CA), and tend to include obsolete words that are not attested in current usage. We address this problem by building a large-scale, corpus-based lexical database that is representative of MSA. We use an MSA corpus of 1,089,111,204 words, a pre-a...

The paper presents a model of lexical ontology, based on SBVR representations, which is related to domain ontology used for semantic search in Lithuanian Internet corpus. The advantage of using SBVR based lexical ontology is the support of various relations among different types of meanings and representations, considering phrases instead of single words, and possibility of transformations to (...

A range of approaches to the representation of lexical semantics have been explored within Computational Linguistics. Two of the most popular are distributional and knowledgebased models. This paper proposes hybrid models of lexical semantics that combine the advantages of these two approaches. Our models provide robust representations of synonymous words derived from WordNet. We also make use ...