NLP

This study extracted and analyzed the linguistic speech patterns that characterize Japanese anime or game characters. Conventional morphological analyzers, such as MeCab, segment words with high performance, but they are unable to segment broken expressions or utterance endings that are not listed in the dictionary, which often appears in lines of anime or game characters. To overcome this challenge, we propose segmenting lines of Japanese anime or game characters using subword units that were proposed mainly for deep learning, and extracting frequently occurring strings to obtain expressions that characterize their utterances. We analyzed the subword units weighted by TF/IDF according to gender, age, and each anime character and show that they are linguistic speech patterns that are specific for each feature. Additionally, a classification experiment shows that the model with subword units outperformed that with the conventional method.

Programarea neuro lingvistica presupune ca limbajul non-verbal că poate fi descifrat prin sistemul reprezentațional VAKOG. Conform teoriei sistemului VAKOG fiecare persoană are un mod dominant pentru reprezentarea internă a realității (vizual, auditiv, kinestezic, olfactiv și gustativ) și că, dacă folosim cuvinte care să corespundă acesteia, comunicarea noastră cu persoana în cauză se va îmbunătăți.

Natural Language Processing is a programmed approach to analyze text that is based on both a set of theories and a set of technologies. This forum aims to bring together researchers who have designed and build software that will analyze, understand, and generate languages that humans use naturally to address computers.

This paper presents a new approach for knowledge extraction from patent document for the use of design engineers. It is based on the Inventive Design Method (IDM) which derives from TRIZ, the theory of inventive problem solving whose goal is to theorize on the act of inventing partly on the bases of patent's observation. The purpose of this paper is to demonstrate that it is possible to automatically extract IDM concepts from patent document, using generic linguistic markers. This paper is the continuation of a previous work and mainly focuses on the retrieval of parameters which characterize the main components of contradictions related to an artifact evolution bottlenecks.

The report addresses the basic problems of the Arabic language formalization based on analysis of linguistic errors in software products. Reviewing the principles of modern information systems operation the authors come to the conclusion that the existing methods of the Arabic formalization allow to note a shift towards the technological aspects of the linguistic processing of facts, however, the quality of applied linguistic components still remains poor. Possibilities for the application of traditional recognition algorithms for Arabic are still uncertain in spite of a significant number of theoretical and practical results in the field of computational linguistics. There are several problems which are due to be solved in relation to the processing of the Arabic text. These issues may be divided into those related to Optical Recognition of the Written Text (OCR), Word Processing (WP) and building of the content of the dictionaries, Machine Translation (MT).

Punjabi language is most widely spoken language of Pakistan (Abbas, Chohan, Ahmed, & Kaleem, 2016). Punjabi is under developed language because of which, upcoming generations are shifting to other technically and digitally developed languages such as Urdu and English. In result of which, the sound shift is being observed in Punjabi language. Sounds which used to be present in the past in Punjabi language are found missing now. This leads to a problematic situation that this sound shift may result in language extinction and sound loss. This study is about the sound change and it has been studied in Punjabi language. On the basis of observation of speech in surrounding, researcher made a hypothesis that those speakers of Punjabi language who acquired Punjabi as L1 are able to produce few distinctive sounds that are not produced by the speakers who acquired Urdu as a mother tongue. For this purpose, a corpus of 2 million words was collected and the words including the sounds |n| ‫ن‬ an...

Most coreference resolution models determine
if two mentions are coreferent using a single
function over a set of constraints or features.
This approach can lead to incorrect decisions
as lower precision features often overwhelm
the smaller number of high precision ones. To
overcome this problem, we propose a simple
coreference architecture based on a sieve that
applies tiers of deterministic coreference models
one at a time from highest to lowest precision.
Each tier builds on the previous tier’s entity cluster output. Further, our model propagates global information by sharing attributes (e.g., gender and number) across mentions in the same cluster. This cautious sieve guarantees that stronger features are given precedence over weaker ones and that each decision is made using all of the information available
at the time. The framework is highly modular: new coreference modules can be plugged in without any change to the other modules. In spite of its simplicity, our approach outperforms many state-of-the-art supervised and unsupervised models on several
standard corpora. This suggests that sieve based approaches could be applied to other NLP tasks.

Dr. Dheeraj Mehrotra, leading academician has published his book on "NLP FOR TEACHERS", keeping Innovation in education as a periodic inception of Quality. The excellence framework of teaching as an expertise and with high demand for innovation in teaching, the publication of NLP FOR TEACHERS is the need of the day. The author has initiated the cause of quality mantras and practices of Neuro Linguistic Programming. The book is one and only book on NLP FOR TEACHERS by any INDIAN author and is expected to empower the TEACHERS towards WOW teaching scenario within classrooms. The book NLP for TEACHERS empowers teachers to rediscover the power of teaching via human excellence towards Quality Literacy for all. It is a means to manipulate human-building approaches via tools of Neuro-Linguistic Programming (NLP), as practice for developing Total Quality Student (TQS) as one of the initiatives of any school with the approach of unleashing the power of success and happiness for teachers, students and parents, in particular. The author, Dr. Dheeraj Mehrotra, encapsulates his wide experience of over thirty years of teaching and learning to pace the quality initiatives of WOW feature for schools, making every student a PRIDE to the human race, with the power of human excellence as a priority to face the model challenges of tomorrow, with a smile on their faces.

Book review available at:

https://notionpress.com/read/nlp-for-teachers

In this paper, we introduce EVALution 1.0, a dataset designed for the training and the evaluation of Distributional Semantic Models (DSMs). This version consists of almost 7.5K tuples, instantiating several semantic relations between word pairs (including hypernymy, synonymy, antonymy, meronymy). The dataset is enriched with a large amount of additional information (i.e. relation domain, word frequency, word POS, word semantic field, etc.) that can be used for either filtering the pairs or performing an in-depth analysis of the results. The tuples were extracted from a combination of ConceptNet 5.0 andWordNet 4.0, and subsequently filtered through automatic methods and crowdsourcing in order to ensure their quality. The dataset is freely downloadable. An extension in RDF format, including also scripts for data processing, is under development.

In this digital world, artificial intelligence has provided solutions to many problems, likewise to encounter problems related to digital images and operations related to the extensive set of images. We should learn how to analyze an image, and for that, we need feature extraction of the content of that image. Image description methods involve natural language processing and concepts of computer vision. The purpose of this work is to provide an efficient and accurate image description of an unknown image by using deep learning methods. We propose a novel generative robust model that trains a Deep Neural Network to learn about image features after extracting information about the content of images, for that we used the novel combination of CNN and LSTM. We trained our model on MSCOCO dataset, which provides set of annotations for a particular image, and after the model is fully automated, we tested it by providing raw images. And also several experiments are performed to check effici...

Published in Dacoromania Litteraria, no. 3, 2016: 10-44 http://www.dacoromanialitteraria.inst-puscariu.ro/ro/nr3.php

The article examines the concept of contemporary community as commoning, at the intersection of action, performance or participatory art, place, site-specific, and (post)digital poetry. This involves a brief review of traditional avant-gardes, 20th century engaged art, and recent political-art movements.  In the process of this analysis, the participatory emerges as a subtler, more nuanced, and less predictable phenomenon than usually accepted. Also, performative subjectivity is traced as either the source of anticommunal community (in French theory), or mere Christian-capitalist construct (in communist philosophy). Agamben’s theory of the coming community is therefore examined as possible response to both these stances, with its relevance to contemporary movements, including post-Occupy. Commoning—paralleled to placing in poetry—turns out to be of critical importance in present-day community especially with correlatives such as displacement and undecidablility. Place, space, and map(ping) are therefore radically redefined in the context, and contemporary poetry appears to be indissolubly related to the process: the poem of place is the place, and poetry becomes the site of the com(mon)ing community. Site (and discourse)-specificity in poetry occasions a shift in focus to digital space, its sonic economy, and the communities and floating locations/sites thereof. Site and discourse fluidity have brought about a paradigm in which the poem and its related apps tend to expand and turn into digital space itself, while in more recent postdigital evolutions, a new political concern for the ‘real’ reshape community, site, and performance/participatory art or poetry in a continuous interactivity and interdependence.

Keywords: community, commoning, participatory art, performance studies, poetry of place, site-specificity, digital space, digital humanities, e-literature, the postdigital, GSI, NLP.

The present paper describes a three stage technique to parse Hindi sentences. In the first stage we create a model with the features of head words of each chunk and their dependency relations. Here, the dependency relations are inter-chunk dependency relations. We have experimentally fixed a feature set for learning this model. In the second stage, we extract the intra-chunk dependency relations using a set of rules. The first stage is combined with the second stage to build a two-stage word level Hindi dependency parser. In the third stage, we formulate some rules based on features and used them to post-process the output given by the two-stage parser. 1

The paper defines and shows how to use the Minimal Ratio – an exact metric that expresses the ratio between the measured value and the limits of the confidence interval calculated according to the formula Fischer’s exact test is based on. The metric is meant to assist with keywords and collocations extraction and comparing texts or corpora according to the word types distribution or other similar criteria.

Energy is a vital input for social and economic development. As a result of the generalization of agricultural, industrial and domestic activities the demand for energy has increased remarkably, especially in emergent countries. This has meant rapid grower in the level of greenhouse gas emissions and the increase in fuel prices, which are the main driving forces behind efforts to utilize renewable energy sources more effectively, i.e. energy which comes from natural resources and is also naturally replenished. Despite the obvious advantages of renewable energy, it presents important drawbacks, such as the discontinuity of generation, as most renewable energy resources depend on the climate, which is why their use requires complex design, planning and control optimization methods. Fortunately, the continuous advances in computer hardware and software are allowing researchers to deal with these optimization problems using computational resources, as can be seen in the large number of optimization methods that have been applied to the renewable and sustainable energy field. This paper presents a review of the current state of the art in computational optimization methods applied to renewable and sustainable energy, offering a clear vision of the lastest research advances in this field.

Low-density languages are also known as lesser-known, poorly-described, less-resourced, minority or less-computerized language because they have fewer resources available. Collection and annotation of a voluminous corpus for the purpose of NLP application for these languages prove to be quite challenging. For the development of any NLP application for a low-density language, one needs to have an annotated corpus and a standard scheme for annotation. Because of their non-standard usage in text and other linguistic nuances, they pose significant challenges that are of linguistic and technical in nature. The present paper highlights some of the underlying issues and challenges in developing statistical POS taggers applying SVM and CRF++ for Sambalpuri, a less-resourced Eastern Indo-Aryan language. A corpus of approximately 121 k is collected from the web and converted into Unicode encoding. The whole corpus is annotated under the BIS (Bureau of Indian Standards) annotation scheme devised for Odia under the ILCI (Indian Languages Corpora Initiative) Project. Both the taggers are trained and tested with approximately 80 k and 13 k respectively. The SVM tagger provides 83% accuracy while the CRF++ has 71.56% which is less in comparison to the former.

Generally, computer system is handled by the English language only. But the person who is unaware of the English language and structure of query language cannot handle the system. This paper proposed a new approach for accessing the database easily without knowing English. So, the database is accessed with the help of natural languages such as Hindi, Marathi etc. Natural language processing (NLP) is the study of mathematical and computational modeling of various aspects of language and the development of a wide range of systems. Natural Language Processing holds great promise for making computer interfaces that are easier to use for people, since people will be able to talk to the computer in their own language, rather than learn a specialized language of computer commands.

Lemmario, Rimario e Concordanze della Divina Commedia e dei principali canzonieri del Duecento e del Trecento.

Opzioni di ricerca:
a) occorrenze di una forma data: classica ricerca per identità di stringhe
b) occorrenze di un lemma (in tutte le sue forme riscontrabili nel corpus): cuore >Forme: cuore, cor, cuori, cori
c) occorrenze di una data categoria grammaticale: cuori : s.m. pl.
d) co-occorrenza (concordanze) di forme o di lemmi: cuore + gentile + amore
e) ricerca di parole con un dato valore semantico: persona, luogo, enti mitologici, animale, vegetale, movimento...
f) combinazione di filtri: per es. Categoria='Nome proprio' e Semantica='Luogo': Roma, Val Camonica, Po, Fiorenza [Firenze]...

This paper describes an experimental, strengths-based program for the treatment of substance abusing offenders under criminal justice supervision in the United States Probation Department. The program is based upon new physiological evidence that links addictions to the experience of hope, and consistent research that identifies self-efficacy, futurity and self-esteem as crucial elements in recovery. Rooted in concepts taken from Jungian and Maslowian ideas of the Self, the program uses techniques gleaned from Neuro-linguistic Programming (NLP) and Ericksonian hypnosis to provide a continuing sense of Self and the possibility of positive, self-actualizing futures. This article explores the theoretical background of the program, specific tools employed, program results and suggestions for further research.

The paper deals with the concepts of fragmentation and reconstruction in the field of portraiture. Taking a portrait as a large fragment of information, we look into ways in which it can be optimised and reduced such that it remains valid but becomes more efficient. The paper commences by exploring the concept of the fragment from various facets, including historically, especially from the modernist point of view, and goes forth to investigate various techniques from practices both adjunct and outside of the field of art in order to inform the portraiture process itself on how information can be collected, optimised and presented to the viewer.

After the success of human genome project, proteome is a new emerging field of biochemistry as it provides the knowledge of enzymes (proteins) interactions with different body organs and medicines administrated into human body. Therefore, the study of proteomics is very important for the development of new and effective drugs to control many lethal diseases. In proteomics study, analyses of proteome is essential and significant from the pathological point of views, i.e., in several serious diseases such as cancer, Alzheimer's disease and aging, heart diseases and also for plant biology. The separation and identification of proteomics is a challenging job due to their

(Available also  .doc older version written in Arabic)
"Since 1997, the MS Arabic spell checker was integrated by Coltec-Egypt in the MS-Office suite and till now many Arabic users find it worthless.
In this study, we show why the MS-spell checker fails to attract Arabic users. After spell-checking a document (10 pages - 3300 words in Arabic), the assessment procedure spots 78 false positive errors. They reveal the lexical resource flaws: an unsystematic lexical coverage of the feminine and the broken plural of nouns and adjectives, and an arbitrary coverage of verbs and nouns with prefixed or suffixed particles.
This unsystematic and arbitrary lexical coverage of the language resources pinpoints the absence of a clear definition of a lexical entry and an inadequate design of the related agglutination rules. Finally, this assessment reveals in general the failure of scientific and technological policies in big companies and in research institutions regarding Arabic.
"

This paper presents methodologies involved in text normalization and diphone preparation for Bangla Text to Speech (TTS) synthesis. A Concatenation based TTS system comprises  basically two modules-  one is natural language processing and the other is Digital Signal Processing (DSP). Natural language processing deals with converting text to its pronounceable  form, called Text Normalization and the diphone selection method based on the normalized text is called Grapheme to Phoneme (G2P) conversion.  Text normalization  issues addressed in this paper include tokenization, conjuncts, null modified characters, numerical words, abbreviations  and  acronyms.  Issues related with diphone preparation include diphone categorization, corpus preparation,  diphone  labeling and  diphone selection. Appropriate rules and algorithms are proposed to tackle all the above mentioned issues.  We developed a  speech synthesizer for Bangla using diphone based concatenative approach which is demonstrated to produce much natural sounding synthetic speech.

Hate speech and fringe ideologies are social phenomena that thrives on-line. Members of the political and religious fringe are able, via the Internet, to propagate their ideas with less effort than in traditional media. In this article we attempt to use linguistic cues such as parts of speech occurrence in order to distinguish the language of fringe groups from strictly informative sources. The aim of this research is to provide a preliminary model for identifying deceptive materials on-line. Examples of such would include aggressive marketing and hate speech. For the sake of this paper we aim to focus on the political aspect. Our research has shown that information about sentence length and the occurrence of adjectives and adverbs can provide information for the identification of differences between the language of fringe political groups and mainstream media.

The information resulting from the use of the organization's products and services is a valuable resource for business analytics. Therefore, it is necessary to have systems to analyze customer reviews. This article is about categorizing and predicting customer sentiments. In this article, a new framework for categorizing and predicting customer sentiments was proposed. The customer reviews were collected from an international hotel. In the next step, the customer reviews processed, and then entered into various machine learning algorithms. The algorithms used in this paper were support vector machine (SVM), artificial neural network (ANN), naive bayes (NB), decision tree (DT), C4.5 and k-nearest neighbor (K-NN). Among these algorithms, the DT provided better results. In addition, the most important factors influencing the great customer experience were extracted with the help of the DT. Finally, very interesting results were observed in terms of the effect of the number of features on the performance of machine learning algorithms.

The article introduces discourse analysis as a fruitful approach to psychotherapy change-process research. Extracts are presented from a successfully resolved, client-specified, problematic theme that was selected from a successful 8-session psychodynamic-interpersonal therapy of a female client presenting with a major depressive episode. The study offers a heuristic demonstrating (a) how resolution of the client's problem evolved from implications raised by the client's own description of her predicament and involved the therapist's legitimation of a morally defensible account of the client's actions and (b) how cultural meanings can be brought into the consulting room as intimately personal problems. The implications of studying therapeutic change as a discursive activity comprising the use and negotiation of sociocultural meanings are discussed.

In chapter 10, Linday Finlay writes with Anna Madill , to describe and explain some different ways to analyse data. Four contrasting types of analysis are outlined with practical exemplars: narrative, thematic, discursive and creative. Each type of analysis highlights different aspects and so enables different insights. As such, qualitative analysis is always tentative, partial and emergent....

I was pleased to be invited to provide this article because it gives me the opportunity to share with my NLP colleagues how useful transactional analysis can be when the two approaches are combined. I often think of it as the Enneagram  model of nine personality types lets us know the nature of our real essence, transactional analysis helps us understand how we lost touch with that, and NLP helps us make changes to get back to our real selves. All three approaches are of course comprehensive in their own right so all I can hope to do here is share a few ideas about the links I see between some of the TA and NLP concepts.

In Your Hands: NLP in ELT by Jane Revell and Susan Norman is an attractive book which presents the core concepts and principles of Neuro-linguistic Programming (NLP).  For those who may not already know, NLP is an approach that is dedicated to modeling exceptional performance in various fields.  In other words, it is the art and science of human excellence.  The authors begin with an overview of NLP and suggestions for getting the most out of NLP, the book and learning/teaching success.
Handing Over: NLP-based activities for language learning by Jane Revell and Susan Norman is the practically oriented follow-up to their first book In Your Hands: NLP in ELT.  Their latest book will help anyone to become more aware of their own and others’ greater potential for learning and specifically answers the question: “yes, but ... what do I actually do with NLP in the classroom.” (p. 3)

Arabic Morphological Analyzer (Including Stemming and Root Extraction) and Part-Of-Speech Tagger

Qutuf (قُطُوْف): An Arabic Morphological analyzer and Part-Of-Speech tagger as an Expert System.

Qutuf is aimed to be the Core of a Framework for Arabic NLP (Natural Language Processing)

At Qutuf, some new concepts have been identified and implemented. Like First Normalization and Second Normalization text forms at the preprocessing phase and the Premature and Overdue Tagging at the Part-Of-Speech tagging task. Moreover, the POS tagging is designed and implemented as a rule-based expert system. A POS tagset, which is built based on a morphological feature tagset, has been designed and used in Qutuf.

Morphological Analysis Includes both Stemming (light stemming) and Root Extraction (heavy stemming). It achieves this by using finite state automates and rules for agreement developed for cliticization parsing. It also uses AlKhalil Morpho Sys open source database for root extraction, pattern matching, morphological feature and POS assignment and closed nouns after enriching it.

Język oparty na zmysłach jest potężnym narzędziem w porozumiewaniu się i wywieraniu wpływu na innych. Człowiek nieodmiennie używa języka odpowiadającego preferowanemu przez niego systemowi reprezentacji.
Tę samą myśl ludzie wyrażają różnym językiem w zależności
od tego jakie systemy reprezentacji wykorzystują.
Zdolność do precyzyjnego użycia języka jest podstawą profesjonalnej komunikacji. Użycie precyzyjnych słów które niosą odpowiednie znaczenie dla drugiej osoby oraz definiowanie co ktoś ma na myśli wypowiadając
określone słowa są bezcenną umiejętnością w komunikacji.
Zestaw pytań, który umożliwia precyzyjne porozumiewanie się jest pierwszym modelem stworzonym w NLP przez Richarda Bandlera i Johna Gryndera w 1975 roku i nosi nazwę modelu meta (słowo meta pochodzi z języka greckiego i znaczy ponad, poza lub na innym poziomie). Model meta to seria pytań - niektóre są oczywiste, używane bez zastanowienia,
inne bardziej wyrafinowane, wszystkim jednak przyświeca
jeden cel - odtworzenie informacji, które zostały pominięte, zniekształcone i zgeneralizowane.
Przeciwieństwo metamodelu nazwano modelem Miltona. O ile metamodel pozwala odczytać powierzchniową strukturę nadawanego komunikatu o tyle model Miltona sięga do głębokiej (podświadomej) struktury języka w procesie komunikowania się poprzez język hipnotyczny, metafory i metakomunikaty. Mówiąc najogólniej jest to umiejętność
stosowania nieprecyzyjnego języka, która pozwala nadawcy przypisywać własne znaczenie słowom jakie wypowiada. Zarówno umiejętność rozpoznawania pominięć, uogólnień, zniekształceń w mowie własnej jak i innych ludzi, jak i umiejętność posługiwania się modelem Miltona ma
ogromny wpływ na jakość komunikacji - sprawny jej przebieg wymaga opanowania obu tych umiejętności.

Citation: Kłusek-Wojciszke, B., Łosiewicz, M. (2009). Programowanie neurolingwistyczne jako nowy paradygmat komunikacji w biznesie (2). Język jako narzędzie porozumiewania się. Studia i Materiały Instytutu Transportu i Handlu Morskiego, 6, 191–200.

Einleitung                       1
Zur Entstehungsgeschichte des NLP       2
Eine erste persönliche Erfahrung mit NLP       3
Eine erste inhaltliche Begegnung       4       
Erster Ausbildungsversuch       5         
Ein zweiter Versuch               5
NLP – interne Kritik                       6
Vermarktungsaspekte               7
NLP und Wissenschaft                 8
Resumee und Ausblick                 9
Literaturhinweise und einige andere Informationen    10

How can an evangelist convert a hardboiled sophisticate? Why does a POW sign a "confession" that he knows is false? How is a criminal pressured into admitting his guilt? Do the evangelist, the POW's captor, and the policeman use similar methods to gain their ends? These and other compelling questions are discussed in the definitive work by William Sargant, who for many years until his death in 1988 was a leading physician in psychological medicine.

Effect of neurolinguistic programming training on self-actualization as measured by the Personal Orientation Inventory. (Link) Experiences of young people who have undergone the Lightning Process to treat chronic fatigue syndrome/myalgic encephalomyelitisa qualitative study. (Link) Impact of the application of neurolinguistic programming to mothers of children enrolled in a day care center of a shantytown. (Link) Neurolinguistic programming as an adjunct to other psychotherapeutic/hypnotherapeutic interventions. (Link) Neurolinguistic programming in physician-patient communication. Basic principles of the procedure-examples for application in surgery. (Link) Neurolinguistic programming training, trait anxiety, and locus of control. (Link) Neurolinguistic programming used to reduce the need for anaesthesia in claustrophobic patients undergoing MRI. (Link) Psychotherapy impact on effectiveness of in-hospital physical rehabilitation in patients with acute coronary syndrome. (Link) Social anxiety and training in neurolinguistic programming. (Link) The Effects of Clinical Hypnosis versus Neurolinguistic Programming (NLP) before External Cephalic Version (ECV): A Prospective Off-Centre Randomised, Double-Blind, Controlled Trial. (Link) Treatment outcome in tobacco dependence after nicotine replacement therapy and group therapy. (Link) Using an imaginary scrapbook for neurolinguistic programming in the aftermath of a clinical depression: a case history. (Link) Weight maintenance through behaviour modification with a cooking course or neurolinguistic programming. (Link) Details  Journal Article  Appel, P. Matching of representational systems and interpersonal attraction Appel, P. (1983): "Matching of representational systems and interpersonal attraction." (United States International University) Doctoral dissertation Dissertation Abstracts International, 43, 3021B(University Microfilms No. 83-018, 35) Details  Thesis  Arrigo, Beth A hermeneutic-phenomenological investigation of the process of changing limiting beliefs about the self in reimprinting Arrigo, Beth (1998): "A hermeneutic-phenomenological investigation of the process of changing limiting beliefs about the self in reimprinting." Details  Thesis  Atwater, John M. Differential effects of interventions from the neuro-linguistic programming meta-model and general systems in early psychotherapy Atwater, John M. (1984): "Differential effects of interventions from the neuro-linguistic programming meta-model and general systems in early psychotherapy." (Atwater, John M.: Details  Thesis  Baab, Kirt J.

ED377009 - Ericksonian Approach to Experiential Education, Part 1: Developing the Stance of the Practitioner; Part 2: Tailoring Interventions; Part 3: Applying Specific Ericksonian Techniques. ... Ericksonian Approach to Experiential Education, Part 1: Developing the ...

Text can be analysed by splitting the text and extracting the keywords .These may be represented as summaries, tabular representation, graphical forms, and images. In order to provide a solution to large amount of information present in textual format led to a research of extracting the text and transforming the unstructured form to a structured format. The paper presents the importance of Natural Language Processing (NLP) and its two interesting applications in Python Language: 1. Automatic text summarization [Domain: Newspaper Articles] 2. Text to Graph Conversion [Domain: Stock news]. The main challenge in NLP is natural language understanding i.e. deriving meaning from human or natural language input which is done using regular expressions, artificial intelligence and database concepts. Automatic Summarization tool converts the newspaper articles into summary on the basis of frequency of words in the text. Text to Graph Converter takes in the input as stock article, tokenize them on various index (points and percent) and time and then tokens are mapped to graph. This paper proposes a business solution for users for effective time management.

Sana'ani Dialect to Modern Standard Arabic: Rule-based Direct Machine Translation

ICAI'11 Vol I -  ISBN #:  1-60132-183-X
ICAI'11 Vol II -  ISBN #:  1-60132-184-8
ICAI'11 Set -    ISBN #:  1-60132-185-6

Authors: Yahya Alamlahi, Fateh Ahemd, Dr. Ghaleph Aljafari