Morphological analyzers (MA) are automated systems that (1) derive the root word of a transformed word, (2) identify the affixes used and (3) identify the change in semantics after the word transformation. MAs are used in the field of natural language processing and information retrieval systems to reduce the size of its word dictionary or lexicon, while being able to efficiently analyze the sy...

Neural network techniques are widely applied to obtain high-quality distributed representations of words, i.e., word embeddings, to address text mining and natural language processing tasks. Recently, efficient methods have been proposed to learn word embeddings from context that captures both semantic and syntactic relationships between words. However, it is challenging to handle unseen words ...

This research focused on the morphological structure in Jason Mraz’s songs. study used theory of Rochelle hypothesis (2009) and examined morphemes found songs their structure. The were obtained directly from Google. applied a qualitative method. data analyzed by reading lyrics songs, underlining word word, identifying words classing them into morphemes, calculating each to find out frequency fr...

In this paper, we propose three novel models to enhance word embedding by implicitly using morphological information. Experiments on word similarity and syntactic analogy show that the implicit models are superior to traditional explicit ones. Our models outperform all state-of-the-art baselines and significantly improve the performance on both tasks. Moreover, our performance on the smallest c...

The analysis of sentiments, emotions, and opinions in texts is increasingly important in the current digital world. The existing lexicons with emotional annotations for the Portuguese language are oriented to polarities, classifying words as positive, negative, or neutral. To identify the emotional load intended by the author, it is necessary to also categorize the emotions expressed by individ...

Since written Chinese does not use blank spaces to indicate word boundaries, segmenting Chinese texts becomes an essential task for Chinese language processing. Besides word segmentation, we also need to identify the part-of-speech (POS) tags of the words. The segmentation and POS tagging process are denoted as morphological analysis. During the process of word segmentation, two main problems o...

We present a comparative investigation of word representations for part-of-speech (POS) and morphological tagging, focusing on scenarios with considerable differences between training and test data where a robust approach is necessary. Instead of adapting the model towards a specific domain we aim to build a robust model across domains. We developed a test suite for robust tagging consisting of...

We present an unsupervised, language agnostic approach for exploiting morphological regularities present in high dimensional vector spaces. We propose a novel method for generating embeddings of words from their morphological variants using morphological transformation operators. We evaluate this approach on MSR word analogy test set (Mikolov et al., 2013d) with an accuracy of 85% which is 12% ...

Languages with rich inflectional morphology exhibit lexical data sparsity, since the word used to express a given concept will vary with the syntactic context. For instance, each count noun in Czech has 12 forms (where English uses only singular and plural). Even in large corpora, we are unlikely to observe all inflections of a given lemma. This reduces the vocabulary coverage of methods that i...