NLPIR

Any Text Classification (TC) problem need pre-processing steps which may affect the classification accuracy. Especially pre-processing steps need substantial effort particularly in agglutinative languages such as Turkish. In this context, a traditional ...

Most research in investigating computer professionals and laypersons' attitudes toward artificial intelligence (AI) are limited to online or offline surveys. This paper analyzes computer professionals' and laypersons' attitudes toward AI by using a ...

Authorship attribution is an important field in online security. Recently there have been numerous successful works in authorship attribution in various European languages. Character n-grams are reported to be the best choice in authorship attribution, ...

At present, the network pyramid scheme has become a major tumor that hinders social development. In order to curb the propagation of the network pyramid scheme and effectively identify the pyramid scheme text in the network, this study proposes a joint ...

A word is the smallest item in Natural Language Processing. However, there is no obvious boundary for Chinese words. How to segment Chinese words always obstructs Chinese researches and applications. Nowadays, a neural network model, Seq2Seq with LSTM, ...

Text classification is one of the most important tasks in natural language processing and information retrieval due to the increasing availability of documents in digital form and the ensuing need to access them in flexible ways. By assigning documents ...

Millions of people with severe speech disorders around the world may regain their communication capabilities through techniques of silent speech recognition (SSR). Using electroencephalography (EEG) as a biomarker for speech decoding has been popular ...

There are many learning methods presented. How could learners know which method is suitable for their learning style? In this paper, we have the objective to classify learning style base on the VARK model using Blended learning method on media creation, ...

In this work, we investigate three types of deep speaker embedding as text-independent features for speaker-targeted speech recognition in cocktail party environments. The text-independent speaker embedding is extracted from the target speaker's ...

We propose deep learning in word embedding for making a diagnostic prediction model. One factor that causes uncertainties in diagnostic is the inexperience of physicians. The diagnosis errors lead to incorrect and delay in treatment, waste of time and ...

Sentiment analysis is considered an important downstream task in language modelling. We propose Hierarchical Attentive Network using BERT for document sentiment classification. We further showed that importing representation from Multiplicative LSTM ...

In this paper, word-frequency distribution of JACET 8000 basic words and text statistics were researched to compare and analyze differentials of English compositions (essays) written by native speakers and non-native speakers. As for the native speakers'...

Myanmar word segmentation is an important task for construction of dictionary file for Myanmar information retrieval and Myanmar text compression. Although Myanmar word segmentation using dictionary and orthography has been existed for Myanmar language, ...

This paper proposes a method to solve the problem of extracting contents from a resume, especially for Indonesian resumes using segmentation method by header followed by models for each corresponding headers. An end to end resume extraction system is ...

In this research, we aim at the construction of a system which detects, points out and corrects speech error (slip of the tongue) of a human speech that occurs in a dialogue system (example: Pepper, Amazon Echo, Google Home) and a human dialogue. In the ...

The massive size of available biomedical literature requires researchers to utilize novel big data technologies in data storage and analysis. Among them is cloud computing which has become the most popular solution for big data applications in industry. ...

Traditional conversational chatbots usually adopt a retrieved-based model. Developers have to provide a large amount of conversational data and classify those data to different intents. To avoid cumbersome development processes, we propose a method to ...

Users have specific information needs which are expressed in short queries to information retrieval systems. The queries are unstructured, and they tend to be short and ambiguous in most cases. Using the shallow language statistics including ...

We develop an innovative personalized recommendation system called KELDEC that links the notes that students take in class with their outdoor experiences captured with camera, to suggest websites that extend their knowledge. Despite the plethora of ...

This paper presents a hybrid method for normalizing written text often found on newspapers to its spoken form. To normalize raw text with a number of non-standard words (NSWs), a two-step model is proposed. The first step involves classifying NSWs into ...

This paper presents a simple but effective method to improve the quality of WordNet synsets and extract glosses for synsets. We translate the Princeton WordNet and other intermediate WordNets to a target language using a machine translator, then the ...

Many research describes Textual Entailment model for compare pair of the sentence but two sentences in term of the poem content consistency are not the same. The content consistency is very important for storytelling in Thai poem composing. In this ...

This paper aims to discover topics from an Indonesian online shop chat. Moreover, we employed Latent Dirichlet Allocation to find out what kind of topics that are often discussed and conversation trends between buyers and customer service. Several tasks ...

Parallel corpus is a critical resource in machine learning based translation. The task of collecting, extracting, and aligning texts in order to build an acceptable corpus for doing translation is very tedious most especially for low-resource languages. ...

In general, higher education is an important step in preparing a career for students in the future. Graduates should have qualifications that are recognized by both entrepreneurs and society. Therefore, every higher educational institution should make ...

It is possible to include complicated structures into an individual syntactic tree, to enhance the usefulness of parsed text corpus. In this part, existing works on Thai treebank construction have been developed in order to address the lack of high-...

A number of morphology-based word embedding models were introduced in recent years. However, their evaluation was mostly limited to English, which is known to be a morphologically simple language. In this paper, we explore whether and to what extent ...

This paper presents unsupervised method of single document extractive summarization. The main idea behind the method is in selecting sentences based on Word Mover's Distance Similarity between each sentence and set of centroid keywords. This approach ...

Text-representing centroids are investigated method recently used to categorize and compare documents written in European languages. As it will be shown, Asian languages and in particular Thai exhibit completely other language structures. Nevertheless, ...

Nowadays in the modern world, interactive smart dialogs with text or voice are gaining traction as the main digital interaction channel between human and machine. However, most of the current platforms do not support or have not fully developed for ...