András Dobó

• PhD in Computer Science
• University of Szeged

PhD thesis written by András Dobó under the supervision of Prof. Dr. János Csirik (University of Szeged). The thesis was defended in Szeged (Hungary) on the 15th of November, 2019. The doctoral committee comprised of Prof. Dr. Márk Jelasity (University of Szeged), Prof. Dr. András Kornai (Budapest University of Technology and Economics), Prof. Dr....

Measuring the semantic similarity and relatedness of words is important for many natural language processing tasks. Although distributional semantic models designed for this task have many different parameters, such as vector similarity measures, weighting schemes and dimensionality reduction techniques, there is no truly comprehensive study simult...

Both during academic work and everyday life it is usual to come across such situations, where one has to compute the difference between values of a variable. However, this can be done many ways. For example, the comparison of accuracy values of methods for the solution of a scientific problem is usually done by either looking at how much the absolu...

Measuring the semantic similarity and relatedness of words is important for many natural language processing tasks. Although distributional semantic models designed for this task have many different parameters, such as vector similarity measures, weighting schemes and dimensionality reduction techniques, there is no truly comprehensive study simult...

Measuring the semantic similarity and relatedness of words can play a vital role in many natural language processing tasks. Distributional semantic models computing these measures can have many different parameters, such as different weighting schemes, vector similarity measures, feature transformation functions and dimensionality reduction techniq...

Smoothing is an essential tool in many NLP tasks, therefore numerous techniques have been developed for this purpose in the past. One of the most widely used smoothing methods are the Kneser-Ney smoothing (KNS) and its variants, including the Modified Kneser-Ney smoothing (MKNS), which are widely considered to be among the best smoothing methods av...

Recruiting employees is a serious issue for many enterprises. We propose here a procedure to automatically analyse uploaded CVs then prefill the application form which can save a considerable amount of time for applicants thus it increases user satisfaction. For this purpose, we shall introduce a high-recall CV parsing system for Hungarian, English...

Measuring semantic similarity of words is of crucial importance in Natural Language Processing. Although there are many different approaches for this task, there is still room for improvement. In contrast to many other methods that use web search engines or large lexical databases, we developed such methods that solely rely on large static corpora....

Noun compounds are abundant in English and their interpretation is crucial for many natural language processing tasks. We propose a method for automatic two-noun noun compound interpretation that searches for suitable paraphrases in static corpora and then issues Web search engine queries to validate them. Native speakers were recruited to evaluate...