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Failing to identify multi-word expression (MWE) may cause serious problems for many Natural Language Processing (NLP) tasks. Previous approaches heavily depend on language specific knowledge and pre-existing natural language processing (NLP) tools. However, many languages (including Chinese language) have less such resources and tools compared to English. An automatically learn effective features...
When manually testing Web sites humans can go with vague, yet general instructions, such as "add the product to shopping cart and proceed to checkout". Can we teach a robot to follow such instructions as well?In this paper I present a novel model, called semantic usage patterns which allows us to capture the general topics behind the individual steps of interactions. These models can be...
Since the advent of the IoT era, various IoT devices have proliferated, transforming ordinary spaces into smart spaces such as smart home, smart office, and smart building. To provide user-friendly service to people, the majority of previous studies have focused on activity recognition and prediction in singleuser environments such as ambient assisted living (AAL) and activities of daily living (ADL)...
Though there are some works on improving distributed word representations using lexicons, the improper over-fitting of the words that have multiple meanings is a remaining issue deteriorating the learning when lexicons are used, which needs to be solved. An alternative method is to allocate a vector per sense instead of a vector per word. However, the word representations estimated in the former way...
It is still a long way to communicate humans and machines emotionally. There are some tries to provide sentimental conversations among humans and machines. Computational humor is one of research topics in computational linguistics and artificial intelligence. We introduce a new method to generate jokes in a sentence related temporal and spatial contexts for continuous conversations with images. We...
In this paper, we motivate the usage of natural language processing techniques to detect the uncertainty cues in the software architecture documents. As an initial step of our study, we analyzed three real-world software architecture documents and manually retrieved examples of different types of uncertainties. Based on those examples, we formulated the hypothesis on how the communication of software...
Current research, in Natural Language Processing, shows more interest in the under-resourced languages, during last years. Amazigh language is the autochthon language of North Africa. However, until 2011 that it became a constitutionally official language in Morocco, after years of persecution. Amazigh language is still considered as one of the under resourced languages. The question is: “how can...
The growing use of informal social text messages on Twitter is one of the known sources of big data. These type of messages are noisy and frequently rife with acronyms, slangs, grammatical errors and non-standard words causing grief for natural language processing (NLP) techniques. In this study, our contribution is to target non-standard words in the short text and propose a method to which the given...
Testing of product is perform to discover or detect the errors and defects in the developed system. But testing is usually time consuming especially when complex projects are canvass. Testing of a product lead off with generation of test cases. The Test case generation are based on three parts coding, design and specification. The Specification based testing deals with generation of test cases from...
A set of lexical categories, analogous to part-of-speech categories for English prose, is defined for source-code identifiers. The lexical category for an identifier is determined from its declaration in the source code, syntactic meaning in the programming language, and static program analysis. Current techniques for assigning lexical categories to identifiers use natural-language part-of-speech...
Early study tries to use chatbot for counseling services. They changed drinking habit of who being consulted by leading them via intervene chatbot. However, the application did not concerned about psychiatric status through continuous conversation with user monitoring. Furthermore, they had no ethical judgment method that about the intervention of the chatbot. We argue that more reasonable and continuous...
Detecting actions or verbs in still images is a challenging problem for a variety of reasons such as the absence of temporal information and polysemy of verbs which lead to difficulty in generating large verb datasets. In this paper, we propose to first detect the prominent objects in the image and then infer the relevant actions or verbs using Natural Language Processing (NLP)-based techniques. The...
Semantic taxonomies are powerful tools that provide structured knowledge to Natural Language Processing (NLP), Information Retreval (IR), and general Artificial Intelligence (AI) systems. These taxonomies are extensively used for solving knowledge rich problems such as textual entailment and question answering. In this paper, we present a taxonomy induction system and evaluate it using the benchmarks...
Visualization techniques are ways of creating and manipulating graphical representations of data. This could assist human information processing by reducing demands on attention, working memory, and long-term memory. The graphical representation of data is also used in the Web as a mean which conveys an overall message easy to be used by a human mind. At the present time, graphical representations...
Ontology, the shared formal conceptualization of domain information, has been shown to have multiple applications in modeling, processing and understanding natural language text. In this work, we use distributed word vectors out of various recent language models from Deep Learning for semi-automated domain ontology creation for closed domains. We cover all major aspects of Domain Ontology Induction...
Moral foundations theory explains variations in moral behavior using innate moral foundations: Care, Fairness, Ingroup, Authority, and Purity, along with experimental supports. However, little is known about the roles of and relationships between those foundations in everyday moral situations. To address these, we quantify moral foundations from a large amount of online conversations (tweets) about...
A podcast combines the liveliness of a FM radio channel with the economy of internet blog posting. They are especially convenient for scenarios when there is limited internet ability and connectivity for example in the car, the gym, etc. While both the volume and heterogeneity of content is huge it becomes operationally difficult to manually categorize or tag these audio items, thus manage them in...
Aspect Based Sentiment Analysis (ABSA) provides further insight into the analysis of social media. Understanding user opinion about different aspects of products, services or policies can be used for improving and innovating in an effective way. Thus, it is becoming an increasingly important task in the Natural Language Processing (NLP) realm. The standard pipeline of aspect-based sentiment analysis...
Evaluating the clinical similarities between pairwisepatients is a fundamental problem in healthcare informatics. Aproper patient similarity measure enables various downstreamapplications, such as cohort study and treatment comparative effectiveness research. One major carrier for conductingpatient similarity research is the Electronic Health Records(EHRs), which are usually heterogeneous, longitudinal,...
Measuring the similarity between strings plays an increasingly important role in many applications such as information retrieval, short answer grading, and conversational agent software. There has been much recent research interest in applying string similarity within Arabic language applications; however, the use of string similarity in Arabic poses a substantial challenge such as the complexity...
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