منابع مشابه
Unsupervised Morphological Relatedness
Assessment of the similarities between texts has been studied for decades from different perspectives and for several purposes. One interesting perspective is the morphology. This article reports the results on a study on the assessment of the morphological relatedness between natural language words. The main idea is to adapt a formal string alignment algorithm namely Needleman-Wunsch’s to acco...
متن کاملUnsupervised Domain Adaptation based on Text Relatedness
In this paper an unsupervised approach to domain adaptation is presented, which exploits external knowledge sources in order to port a classification model into a new thematic domain. Our approach extracts a new feature set from documents of the target domain, and tries to align the new features to the original ones, by exploiting text relatedness from external knowledge sources, such as WordNe...
متن کاملUnsupervised Text Segmentation Using Semantic Relatedness Graphs
Segmenting text into semantically coherent fragments improves readability of text and facilitates tasks like text summarization and passage retrieval. In this paper, we present a novel unsupervised algorithm for linear text segmentation (TS) that exploits word embeddings and a measure of semantic relatedness of short texts to construct a semantic relatedness graph of the document. Semantically ...
متن کاملUnsupervised morphological parsing of Bengali
Unsupervised morphological analysis is the task of segmenting words into prefixes, suffixes and stems without prior knowledge of language-specific morphotactics and morpho-phonological rules. This paper introduces a simple, yet highly effective algorithm for unsupervised morphological learning for Bengali, an Indo-Aryan language that is highly inflectional in nature. When evaluated on a set of ...
متن کاملUnsupervised Learning of Morphological Forests
This paper focuses on unsupervised modeling of morphological families, collectively comprising a forest over the language vocabulary. This formulation enables us to capture edgewise properties reflecting single-step morphological derivations, along with global distributional properties of the entire forest. These global properties constrain the size of the affix set and encourage formation of t...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Advanced Computer Science and Applications
سال: 2016
ISSN: 2156-5570,2158-107X
DOI: 10.14569/ijacsa.2016.071047