Questions On Natural Language Processing

Questions On Natural Language Processing
Introduction
1.1 Inspiration and Outline
Today in the world of information technology everyone is using internet to share and access data.
But the data is in the form of natural language. And as we all know that all natural languages have
basic feature that it have ambiguity. It is something which can be understand in two or more ways,
and that depends on what situation it occurs. There are different types of ambiguities present in
natural languages like lexical ambiguity, structural or grammatical ambiguity, ambiguity of scope,
pragmatic ambiguity etc. Among all these ambiguities, lexical ambiguity is generally present in
natural languages. This ambiguity can be defined as the ambiguity which occurs because a word has
various meaning. So, to use information technology in best way we need to eliminate ambiguity
from the sentences with the help of tool called word sense disambiguation.
Word Sense Disambiguation (WSD) is a tool which computes the correct sence of ambiguious word
in context which it occur. It is a main challenge in Natural Language Processing(NLP) and it is
considered an AI– complete problem. For example consider the sentence–। and ;g ,d vke ckr gSA
vke Qyks dk jktk gSA Here, the ambiguous word is vke which can be interpreted as 'common' or as
'mango' based on the situation in which it is said.
The problem of recognition of definite sense of given word seems to be simple. As human being
simply identify the meaning of a word given on a given context. But
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Web Intelligence And Its Usefulness
Abstract
In the world of Information Technology (IT), there are many areas and disciplinary of research
available and Web Intelligence (WI) is one of the new sub disciplinary of Artificial Intelligence (AI)
and Advanced IT. When AI and IT is implemented on web it defines WI. WI is used to develop web
– empowered system, Wisdom Web, Web Mining, web site automation, etc. In this paper, detail
discussion is done on Web Intelligence and its usefulness in developing intelligent web. Many
literatures are also discussed related to the Web Intelligence and at the end challenges and problems
faced during the research in the area is also mentioned. This paper will provide the pathway to the
researcher who want to perform research in the field of Web Intelligence.
Keywords – Natural Language Processing, Web Intelligence, Artificial Intelligence, Advanced
Information Technology
I. Introduction
In the era of Information Technology (IT) Web Intelligence (WI) represent new sub disciplinary for
scientific research and development that explores fundamental roles as well as practical impacts of
Intelligence. T. Y. Lin and Yan–Qing Zhang [2] have described Intelligence as" a specific set of
mind capabilities which allow the individual to use the acquired knowledge efficiently and to
behave appropriately in the presence of new tasks and living conditions". With the explosive growth
of internet, wireless network, web database and wireless mobile devices implies intelligence on web.
Y.Y. Yao,

Case Study On Neural Machine Translation
Facebook partnered with Bing in 2011 for translation services, making it an early pioneer in the
move toward neural machine translation.
In December 2015, Facebook dropped Bing and began to outsource its translation services while
developing its own translation technologies.
Facebook's own neural machine translator went fully operational on August 3, 2017.
Overview
Hello and thank you for your question about Facebook neural machine translation. The short version
is that Facebook has been moving toward integrating their own translation technology since 2011,
and have recently (August 2017) gone fully operational with their own Neural Machine Translator.
Below you will find a deep dive of our findings.
METHODOLOGY
Our goal for this ... Show more content on Helpwriting.net ...
Facebook was an early pioneer of online translation when in 2011 it started using automated systems
to translate users' posts and comments in the News Feed. Facebook used Bing initially because they
didn't yet have their own technology.
In January 2015, Facebook open–sourced Torch (their deep learning library). Facebook explains
TORCH as an open source development environment for numerics, machine learning, and computer
vision. Many projects on machine learning and AI at FAIR (Facebook AI Research) use Torch.
Also in 2015, Facebook acquired Wit.ai, a startup using understanding of natural language in
text/voice to power user interfaces.
In December 2015, Facebook dropped Bing and started using its own translation technology. The
issue was that Bing was built to translate more properly written website text, not human slang.
Facebook stated that the disconnect between the languages people speak and the content they want
to connect to on the Internet is what made them want to create their own neural network–based
machine translation (MT) system.
Also in Dec 2015, Facebook opensourced it's hardware designs for anyone to explore through the
Open Compute Project. The server was called BigSur, which is described as servers with graphics
processing units (GPUs), which have become the chip of choice for deep learning.

Later, in June 2016, Facebook stated that Statistical

The And Temporal Information Extraction
Much of the information extraction community early focus on in tasks like named entity
recognition, co–reference and relation extraction, but recently due to the high demand of temporal
information in different NLP application, scholars are focusing on event, temporal and event and
temporal information extraction and the extraction of event and temporal information became a hot
research area. Different scholars involved in event and temporal information extraction researches.
Currently there are a lot of research conducted in event and temporal information extraction in
different domains and languages with different techniques, methods and tools. In this chapter, we
present some of the works conducted in the English language related to this thesis project. The first
work we discuss is called TIE, Temporal Information Extraction system extracts events from text by
inducing as much as temporal information possible. TIE makes global inference, enforcing
transitivity to bound the beginning and finishing time for each event. TIE introduces temporal
entropy as a method to evaluate the performance of temporal IE system. TIE system outperforms in
experiment in three optional approaches. The TIE system uses a probabilistic method to recognize
temporal rations. They use TimeBank data [25] to train the system. TIE processes, each natural
language sentence into two sequential phases. The first phase is responsible for extracting event and
identifying temporal expression and it use a

Common Core Standards Literature Review
Literature Review What is the common core? "The Common Core State Standards (CCSS) defines
the knowledge and skills in English language arts and mathematics that students need for success in
college and careers upon high school graduation" (Santos, Darling–Hammond, Cheuk (2012)). The
common core was created, "to provide clear academic benchmarks with more concise academic
standards for essential learning that will prepare students to be college and career ready" (Liebtag,
E. (2013)). The common core standards have then, been introduced and applied to most schools in
the U.S, and although it may have its controversies, the major issue, is its effect on ELL (English
Language Learners) students. "ELs currently constitute 10 percent of the U.S. ... Show more content
on Helpwriting.net ...
According to Duguay, A., Massoud, L., Tabaku, L., Himmel, J., & Sugarman, J. (2013, September),
"As educators have examined the standards more deeply, concerns have arisen about their
implementation in classrooms with diverse groups of students, including English learners". Not only
this, but the concept of math also has its visible adversities. According to Robertson, K. (2009),
"Although it is easy to assume that many English language learners (ELLs) will excel in math
because math is a "universal language" and students may have had prior educational experience that
included mathematical instruction, that assumption can lead educators astray". Many teachers are
struggling with the, "increasingly rigorous grade–level content instruction; by content area teachers,
many of whom are newly incorporating language development techniques in their subject area
classes" (Duguay, A., Massoud, L., Tabaku, L., Himmel, J., & Sugarman, J. (2013, September)). The
common core may be the stepping for detailed curriculum, but it is seeming that, it "cannot be
tailored to all of the diverse populations of our nation" (Liebtag, E. (2013)). The expectations of the
common core exacerbate the academics for ELL students. According to, HAKUTA, K., SANTOS,
M., & FANG, Z. (2013), "when ELs are isolated for direct language instruction,

Natural Language Generation Essay
Natural Language Generation Abstract Natural language generation is a relatively new field in
computer science. The two main questions to be solved are "what to say" and "how to say it." What
to say includes answering questions not specifically asked by the user, and remembering previous
statements made by the user and by the program itself. How to say it involves construction of logical
sentences, use of pronouns, and sentence fragments. When speech synthesis is used, it also involves
producing intelligible word rhythm, emphasis, and pauses. A new, exciting extension of speech
synthesis is the inclusion of "emotion" in speech. User: ELIZA: Men are all alike In what way?
They're always bugging us ... Show more content on Helpwriting.net ...
Natural language generation can also be used in some expert systems. Another application is in
translation programs. It is probable that many new applications will be developed as natural
language programs are refined. The two main issues in natural language generation are determining
what to say, and determining how to say it. The issue of determining "what to say" quickly spills
over into other areas of Artificial Intelligence, however, a few issues are especially interesting. The
basis of these issues is that natural language is so "natural" to users that they expect, or at least
desire the computer to "think" like a human. This causes users to use imprecise language when
communicating with natural language systems. For example, the following questions were typed to
PLANES, which is a question and answer system delivering information regarding aircraft flights
and maintenance: 1. I request the number of flight hours... 2. I need to know the number of flight
hours... 3. Want number of flight hours... 4. Find the number of... 5. Was any work performed on
Plane 3... The user does not desire the literal interpretation of the above statements. Literal
interpretation would be as follows: 1) No response by the program: the user is making a statement
about what he/she is doing: he/she is requesting information. 2) & 3) No response by the program:
the user is making statement about his personal desires. 4) No

Language As A Natural Language
In our society today, language plays a diverse role in human potential and captures individual unique
human characteristics of expression. Likewise, if a universal language was adopted, these distinctive
perspectives will be lost. In correlation, linguistic and phonological skills were created when people
used language as a natural communication system. Consequently, one's daily life is impacted by
language through unique ways we can communicate to manifest problem–solving and cognitive
skills. Above all, language plays a huge role in cooperation and sharing of ideas throughout the
world. Undeniably, English is considered the dominant language spoken today. However, as time
passed, cultural identities became corrupted and other native ... Show more content on
Helpwriting.net ...
Evidently, the base and growth of human intelligence is within the framework of language. In this
case, language unfolds the social formation which portrays the exchange of ideas, views, emotions,
and value. As a result, complex grammatical skills are formulated to grasp greater communication
structure. In other words, the loss of linguistic diversity would be detrimental because every
language has its own uniqueness that adds to our scientific understanding of grammar and social
skills. According to Grenoble, "If English were the only language on the face of the earth, we could
not know literally hundreds of things which are permitted, even predicted, by universal grammar
and accidentally missing in English, or any other single language." Clearly, there are many words
and phrases that cannot be translated from one language to another. For that reason, the grammatical
principles of multilingualism have critical impact on how we interpret the need to form social
groups and use diagnostic set of problem–solving skills to identify how communication can be
formed. To expand on that, "[g]rammar did not come from a set of rules that are somehow hard–
wired into the brain. It is more likely that humans needed to solve the social problem of ensuring
that everyone understood each other" (Ceriani). In other words, language can be learned

We Propose A Novel Framework For Tweet Segmentation
Abstract–Twitter has become one of the most important communication channels with its ability
providing the most up–to–date and newsworthy information. Considering wide use of twitter as the
source of information, reaching an interesting tweet for user among a bunch of tweets is
challenging. A huge amount of tweets sent per day by hundred millions of users, information
overload is inevitable. For extracting information in large volume of tweets, Named Entity
Recognition (NER), methods on formal texts. However, many applications in Information Retrieval
(IR) and Natural Language Processing (NLP) suffer severely from the noisy and short nature of
tweets. In this paper, we propose a novel framework for tweet segmentation in a batch mode, called
HybridSeg by splitting tweets into meaningful segments, the semantic or context information is well
preserved and easily extracted by the downstream applications. HybridSeg finds the optimal
segmentation of a tweet by maximizing the sum of the stickiness scores of its candidate segments.
The stickiness score considers the probability of a segment being a phrase in English (i.e., global
context) and the probability of a segment being a phrase within the batch of tweets (i.e., local
context). For the latter, we propose and evaluate two models to derive local context by considering
the linguistic features and term–dependency in a batch of tweets, respectively. HybridSeg is also
designed to iteratively learn from confident segments as pseudo

Academic Roles And Academic Leadership
Introduction Many academic advisers sit on the margins within the academy due to the
professionalization, casualization and discursive complexity of the academic language and learning
workforce (Percy, 2011; Stevenson & Kokkinn, 2007). Moreover, academic advisers are also
responsible in providing effective feedback and support to all students internal and external to the
university; some considering feedback being the most important aspect of the assessment practices
(Price, Handley, Millar, & O 'Donovan, 2010). Nevertheless, advisers in drop–in centres across
Australia are time restrained and are limited to the amount of editing and proofreading they are
willing, or able to do. Moreover, EFL/ESL students are in dire need of greater grammatical, editing
and proofreading support and service from the university. Above and beyond the student and the
adviser, tutors further exacerbate the situation by providing feedback to the student as a product
rather than a long term process (Price, Handley, & Millar, 2011). One of the strategies to deal with
this issue is to reconceptualise the objective and role of feedback from advisers and tutors, and to
develop more holistic self–directed and university driven feedback approaches (Merry, Price,
Carless, & Taras, 2013, p. 41). One method to reconceptualise this is the implementation of either a
learning centre specific, or institutionally wide grammar checking program. With the developments
of artificial intelligence, algorithmic

Gigi Acker Eating Smart At Work Case Study
In the wired world, Gigi the personal snack consultant is a wanted woman. Snacks That 'Amp–Up'
Energy A Peek Into the Corporate Pantry Eating Smart at Work Gigi Acker, R.D., is the nutritionist
to the stars of Silicon Valley. She meets one–on–one with employees at major West Coast tech
companies to teach them how to identify cravings, find healthy snacks that actually taste good and
learn to time their eating to continuously energize the body and brain. She works with personalities
ranging from high–flying execs to grass–roots Web monkeys. When Gigi meets them, they're getting
tired and cranky during the workday and they don't know why. But they do know what they want:
maximum energy and smarts for the whole 12–hour (or more) day. Everyone ... Show more content
First, [the protein bar] gives you carbs and protein ... [with the Snickers] you're getting more fat;
nuts are 75 percent fat. High–fat food makes you sleepy if you eat too much of it. And the energy
bar has fiber, which you're not going to find in peanut M&Ms – plus, they're made from whole oats
and dried fruits. There's a difference in how our body reacts to something wholesome vs. sugar,
which our body reacts unpredictably to. FOXNews.com: What are typical client schedules you work
with? Acker: It varies. I have some who ... start the day really early. One client gets up at 5, she's at
the corporate gym at 6 and is eating a low–fat breakfast at 7. She found that by 10 she was starving
and eating what other people brought in, heading to the candy jars ... it was so frustrating. So we
looked at it: She needed a 10 o'clock snack to stay energized. For her, she wanted convenience.
FOXNews.com: Was she looking to lose weight too? Is that a common goal of your

Theme Of Language Devices In The Joy Luck Club
In The Joy Luck Club, language devices such as figurative language, diction, sentence structure, and
significant detail are used to characterize the different characters in the book. These language
devices capture the characters' emotions, personality, qualities of mind, and goals. Amy Tan uses a
variety of language devices to characterize Ying–ying's emotions of sorrow, disconnection, shame,
love, her passive, careless personality, and her quality of mind of determination.
The use of language devices creates Ying–ying's emotions of sorrow and her passive personality and
quality of mind. Throughout the novel, Ying–ying mentions that her daughter Lena and she are
ghosts. The ghost becomes a symbol of passivity, a symbol of not taking action to stop bad things
from happening. The ghost symbol creates Ying–ying's voice by representing her passive personality
and quality of mind. Additionally, the author uses significant pieces of detail. In "The Moon Lady,"
Ying–ying gets lost. She observes her shadow and describes it, "It was shorter this time, shrunken
and wild–looking. We ran together over to some bushes along a walkway and hid" (80). This piece
of detail shows a personality shift in Ying–ying. It describes the changes in Ying–ying's shadow
which represents the change of her restless personality to a passive and silent one. Another language
device used is diction. When introducing "The Moon Lady," Ying–ying says, "And I want to tell her
this: We are lost, she and I, unseen and not seen, unheard and not hearing, unknown by others" (64).
The words "unseen," "unheard," and "unknown" are related to one another at a certain level, and
they create a general picture of Ying–ying's emotion. Ying–ying feels anguish for not doing anything
in her whole life and letting herself become a ghost. The diction also reveals Ying–ying's anguish for
letting her daughter become a ghost like herself.
Language devices capture Ying–ying's emotions of disconnection and her careless personality.
Ying–ying starts to talk about her daughter Lena and the effect her passive personality has on her.
Ying–ying explains how she lived in America, accepting everything that came her way and how she
accepted Lena's American ways. She says,

Symbolism in Bernard Malamud's The Natural Essay
Symbolism in Bernard Malamud's The Natural
The role of symbolism in Bernard Malamud's The Natural is important in helping the reader
understand the theme and meaning of the novel as well as the time period in which it took place.
Malamud¡¦s use of symbolism defines the character of Roy Hobbs and shows how the events
occurring around him affected his decisions and, eventually, his career.
Symbolism in The Natural takes the form of characters, such as women who strongly influenced
Roy; historical events, such as the infamous 1919 World Series scandal; and even Greek and Roman
mythology. All forms of symbolism used by Malamud are woven into the life and career of Roy
Hobbs.
As a first example, women have a tremendous ... Show more content on Helpwriting.net ...
His desperate attitude leads him to be seduced by her, ending his bid to make the Chicago Cubs.
The character of Harriet Bird serves as an ancestor–figure to Iris Lemon and Memo Paris
(Helterman 25). In a way, Iris and Memo are symbolic descendants of Harriet because they, too,
have so much influence on Roy. Memo, however, closely resembles Harriet in personality. Both of
the women are very attracted to two separate major league ball players, Memo having a relationship
with Roy¡¦s teammmate Bump Bailey, and Harriet being attracted to Whammer Wabold on the train.
Both also seem to want to cause Roy harm, doing what they can to stand in the way of his eventual
stardom.
The two truly opposite personalities created by Malamud are Memo and Iris (27). Physically, Memo
is first shown wearing a black dress and has red hair; Iris is shown wearing a red dress with a white
rose attached and has black hair. Mentally, Memo tends to use her memory to live in the past,
relating everything to her deceased lover, Bump. On the other hand, Iris uses substance to live,
describing her life with actions and words rather than by memories. Malamud creates these two
characters to force Roy to choose his fate. For his own benefit and well being, Roy should choose
Iris and stay away from Memo. Memo¡¦s attractiveness and seductiveness, however, keeps Roy from
making the right decision.
Another form of symbolism that influences Roy¡¦s

American Sign Language ( Asl ) Is A Visual And Natural...
American Sign Language (ASL) is a visual and natural language. It is used widely by the members
of the deaf community in the United States (Valli & Lucas, 2000; Andrews, Leigh, & Weiner, 2004).
About 90% of deaf children are born to hearing parents (DOH) (NIDCD, 2015). 10% of deaf
children are born to families with one or both deaf parents (DOD) (Mitchell & Karchmer, 2002).
Deaf children of DOD will use ASL as their primary language rather than spoken English or a
different language such as Spanish, Chinese, or other than English (Mitchell & Karchmer, 2002).
Deaf families understand the importance of having language access early and their deaf children's
vocabulary will be as big comparable to hearing children who are learning a spoken language
(Baker, 2010). Deaf children from DOD have full access to ASL whereas most deaf children from
DOH have limited access to ASL. Deaf children of DOH are typically not given the same early
opportunity (Baker, 2010). Research suggested that the first few years of the deaf child's life are the
most crucial to a child's development of language skills and for establishing successful
communication (NIDCD, 2014). In Texas, there are nine hundred–eighty Early Childhood
Education (ECE) programs that offer either full–day or half–day pre–kindergarten programs (LBB,
2007). One of the ECE is the deaf education program for children who are deaf and hard of hearing.
One setting in the deaf education program is a public school setting. A

Automatic Summarization Of News Articles Using Textrank
AUTOMATIC SUMMARIZATION OF NEWS ARTICLES USING TEXTRANK
ABSTRACT:
With an increase in the amount of information consumed every day, time is a prime resource.
Keeping up with current events is an activity that is essential for everyone, but saving time is also
important. Our paper is mainly focused on the implementation of Natural Language Processing
techniques and algorithms to summarize news articles from public sources such that they can be
consumed in a short amount of time, keeping the user updated of global as well as local events. We
first provide an Introduction by stating problems faced, and an overview of NLP and Automatic
Summarization. We then survey different types of Summarization, and detail a solution using the
TextRank algorithm, along with our proposed implementation.
1. INTRODUCTION:
In today's world time is limited but the information available online is in excess. With the advent of
personal mobile computing devices, we are being presented with a barrage of information every
minute. This makes it increasingly important to consume as much information as possible in the
least amount of time, while eliminating irrelevant and redundant data. News is another domain
which falls prey to this information overload. With the emergence of lightning–fast news delivery
through social media services such as Twitter, Facebook well as various News Sources, It is a dire
need of the day to save time and grasp just enough information that is required about current

Natural Language Processing ( Nlp )
CHAPTER1: INTRODUCTION
Natural Language Processing (NLP) deals with actual text element processing. The text element is
transformed into machine format by NLP. Artificial Intelligence (AI) uses information provided by
the NLP and applies a lot of maths to determine whether something is positive or negative. Several
methods exist to determine an author's view on a topic from natural language textual information.
Some form of machine learning approach is employed and which has varying degree of
effectiveness. One of the types of natural language processing is opinion mining which deals with
tracking the mood of the people regarding a particular product or topic. This software provides
automatic extraction of opinions, emotions and sentiments in text and also tracks attitudes and
feelings on the web. People express their views by writing blog posts, comments, reviews and
tweets about all sorts of different topics. Tracking products and brands and then determining
whether they are viewed positively or negatively can be done using web. The opinion mining has
slightly different tasks and many names, e.g. sentiment analysis, opinion extraction, sentiment
mining, subjectivity analysis, affect analysis, emotion analysis, review mining, etc.
However, they all come under the umbrella of sentiment analysis or opinion mining. Sentiment
classification, feature based sentiment classification and opinion summarization are few main fields
of research predominate in sentiment analysis.
In

Wireless Voice Controlled (Natural Language Processing)
WIRELESS VOICE CONTROLLED (NATURAL LANGUAGE PROCESSING) HOME
AUTOMATION SYSTEM
ABSTRACT
Automation is an upcoming technology of 21st century. The important reason automation gaining its
popularity is reducing human effort, interaction and to reduce human errors. With the improvement
in latest technologies, smartphones have become an essential gadget to all. For 2016, the number of
Smartphone users is forecast to reach 2.1 billion. Another upcoming technology is the natural
language processing which uses human voice for commands. Combining all of these technologies,
the project presents a wireless voice controlled home automation system. Such a system will be
helpful for senior citizens and physically disabled persons who are in need ... Show more content on
Helpwriting.net ...
2. SYSTEM DESIGN
2.1. System Components
2.2. Figure 1: Architecture Diagram of the System
The Voice–operated Android and Arduino Home automation system uses an Android based
Bluetooth enabled phone for its application and the Arduino Uno as the microcontroller. The key
components of this system are:
Android Smartphone
Arduino UNO board
ESP8266 Wi–Fi module
Relays
Light bulbs / LED's
2.2.1. Android Based Phone
Android is a mobile operating system (OS) based on the Linux kernel and currently developed by
Google. With a user interface based on direct manipulation, the OS uses touch inputs that loosely
correspond to real–world actions, like swiping, tapping, pinching, and reverse pinching to
manipulate on–screen objects, and a virtual keyboard. We have used the Android platform because
of its huge market globally and it's easy to use user interface. Applications on the Android phones
extend the functionality of devices and are written primarily in the Java programming language
using the Android software development kit (SDK). The voice recognizer which is an in built
feature of Android phones is used to build an application which the user can operate to automate the
appliances in his house.
2.1.2 Arduino

Arduino is an open source prototyping platform easy to use on software as well as hardware. The
board can programmed to switch on/off electronic appliances using ARDUINO (IDE).
2.1.3 Wi–Fi Module
This allows the Arduino board to connect to android

Space Race Evolution
Even though the Earth has been around for a few billion years, it has been only 200,000 years when
the first homo sapiens, modern human species, came to existence. To put it into perspective, if the
arm length represents the timeline, the shoulder is the Big Bang, the beginning of the finger nail is
when the dinosaurs existed, and the human start to become a possibility right around the tip of the
finger. Even more astounding, industrialization started only in the 1800s, which estimated 200 years
to develop to the current society. The remarkable number is evidence to human extraordinary
intelligence and limitless capabilities to transform ambition into reality; however, any development
will reach to a point where the growth is less significant than it is used to be. This is referred as the
law of diminishing return. Therefore, the research for a more advanced technology, Artificial
Intelligence, or AI, has become the new Space Race of the 21st century. Many ... Show more content
If human hadn't eaten the food the same way the ancestor of over a half million years ago did, which
was to cook them first, it would have taken more than nine hours of eating a day to power the brain.
(15) Cooked foods are pre–digested, softer and easier to swallow, promoting complete digestion and
absorption of nutrients. The same idea applies with allowing AI to take over time consuming and
difficult task. The impact that AI brings far more than just direct consequences. With AI, people
work less and can spend more time exercising, maintaining a balance between physical and mental
health, which prevents stress and lowers the suicide or crime rate. Others can volunteer and help
people in need while some can spend more time with their relatives. The smartest one after all is still
humans. They design machines to do the hard work so they can have more time for

Trends Of E-Commerce Trends
Four Trends That Will Dominate the E–Commerce Industry In 2018 Every year the e–commerce
industry is experiencing a stupendous 20% growth. Last year has been awesome for the e–
commerce industry. New technologies emerged at the end of 2016, flourished and evolved to bring
about a maturity in the entire online retail industry. Definitely, at the end of 2017, this evolved
technology and few emerging technologies in the e–commerce domain will be setting new trends for
2018. Build Your Online Store by Diving into the Happening E–commerce Trends of 2018 The
technology advances in 2018 have brought us where computers can easily augment human
understanding and behavior. Moreover, e–commerce businesses are trying hard to stand out today's
noisy competition by making their online ... Show more content on Helpwriting.net ...
Using AR and VR technology to develop an e–commerce website will involve customers deeply
offering a compulsive 'Immersive' experience. So hold on to your seats, tighten your seat belts and
enjoy the ride to v–commerce because the e–commerce industry will be changing forever.
Conclusion The primary aim of every business is to acquire and retain customers; e–commerce
business is no different. Each year technology evolves compelling us to take a note of it. Coping up
with these trends is beneficial for online businesses because early adoption of latest technology
provides a leading edge over the competition. Inversely neglecting new market and technology
trends will eventually result in a major setback. It is hard to predict the future concerning e–
commerce technology. However, we think these four trends will particularly make an impact in
2018. Regardless of what you are, selling online it is pretty clear that not a single e–commerce brand
can afford to rest on its laurels. Therefore, it's your take whether to keep up with these trends or

Performance For Web Documents Mining Using Nlp And Latent...
A
THESIS
On
Performance for Web document mining using NLP and Latent Semantic Indexing with Singular
Value Decomposition
ABSTRACT
In this thesis we propose a description Web based document file can be say that Latent Semantic
Indexing is a application for information sentence and word based retrieval that promises to offer
better performance by incapacitating approximately limits that waves outdated term identical
methods. These word matching techniques have constantly relied on matching query terms with
document terms to retrieve the documents having terms matching the query terms. However, by use
of these traditional retrieval techniques, user's no need for adequately helped. While users want to
search through information based on conceptual content, natural languages have limited the
expression for such area of study. By Using Cholesky decomposition finds the lower triangular
matrix that satisfies . For instance, with two random variables the decomposition is done as worked.
Although, a determinant of the correlation matrix of the main variables does not have to be positive
and in that case other transformation methods can be applied. NLP (natural language processing)is
used for stemming, stop word and they show problem for polynomial series for the sentence . Due to
these natural language problems, individual words contained in user's queries, may not clearly
specify the intended user's concept that find the result in retrieval of some unrelated

Introduction Of Natural Language Processing
INTRODUCTION TO NATURAL LANGUAGE PROCESSING
What is NLP?
Natural Language Processing can be defined as the use and ability of systems to process sentences
in a natural language such as English, instead of using a specialized artificial computer language
such as C, C++ etc. The systems used for NLP are a digital computer which is similarly resemble to
mainframe and personal computers. The digital computer systems in this fifth generation possesses
artificial intelligence technique and thus able to process natural languages. Natural language is a
more restricted subset of a human language; it cannot be thought of an actual language that
possesses ambiguities which computers could not sort out. Hence it is fair that "Human Languages
grant aberration that natural language cannot grant." In a larger view; Natural Language Processing
includes signal processing or speech recognition, context reference issues and semantic analysis and
processing. Typical applications for Natural Language Processing include the following:
a) A good human computer interface that can translate from a natural language into a computer
language and vice versa. A natural language system can act as an interface to a database system.
This technology is very useful for the blind people; that with the help of speech recognition interact
with computers.
b) A basic necessity is for a translation program that could convert from one human vocal language
to another. This saves down the time for translation.
C)

Side Effects Of Cyber Bullying
Social media is a phrase that we throw around a lot these days, often to describe what we post on
sites and apps like Facebook, Twitter, Instagram, Snapchat and others. The "social" part: refers to
interacting with other people by sharing information with them and receiving information from
them. The "media" part: refers to an instrument of communication, like the internet (while TV, radio,
and newspapers are examples of more traditional forms of media). Social media are web–based
communication tools that enable people to interact with each other by both sharing and consuming
information. However, social media may have some side effects such as cyberbullying, which may
have negative impacts on the life of people, especially children and teenagers. Cyberbullying can be
defined as aggressive, intentional actions performed by an individual or a group of people via digital
communication methods such as sending messages and posting comments against a victim.
Different from traditional bullying that usually occurs at school during face–to–face communication,
cyberbullying on social media can take place anywhere at any time. For bullies, they are free to hurt
their peers' feelings because they do not need to face someone and can hide behind the Internet. For
victims, they are easily exposed to harassment since all of us, especially youth, are constantly
connected to Internet or social media. As reported cyberbullying victimization rate ranges from 10%
to 40%. In the United States,

Natural Language Processing And Machine Learning Techniques
The manuscript at hand presents a framework that implements Natural language processing (NLP)
and machine learning techniques to extract synthesis parameters of metal oxides from a large set of
published articles. The manuscript also presents insights into the key synthesis parameters using
machine learning algorithms. NLP technique is of broad and current interest in many research areas
and it is being extensively used to extract information on a large scale, which is otherwise not
feasible via manual exploration. In the field of chemistry/materials, NLP holds immense promise to
extract useful information the literature, such as extraction of materials properties, processes, and
various synthesis details. However, NLP has not been ... Show more content on Helpwriting.net ...
I believe the current manuscript holds the merit to be published in a high–quality journal, and my
recommendation is to accept the manuscript to be published in Chemistry of Materials. The authors
may want to address the following list of minor issues to further improve the manuscript: 1. Logistic
regression classifier is applied to distinguish paragraphs that are related to synthesis from other non–
synthesis related paragraphs. Applying logistic regression to classify the paragraphs is an elegant
way to determine the synthesis details, however, it might have errors in the classification (95%
accuracy in the current manuscript). A simpler way to classify would be to search for section titles
like 'Methods', 'Materials', 'Methods and materials', etc., and then classify the text in this section as
synthesis paragraphs. It will be worth considering this approach and comparing it with the logistic
regression approach. However, the former technique might not work if the search paper is a review
article. 2. From the description presented in the manuscript, it appears that the data is extracted from
the paragraphs. However, there are articles where the information is presented in the form of
tables/figures. A discussion on the scope of data extraction from tables/figures would be of
significant interest to the chemistry community as large amount of chemical/materials data is
published in this format. 3. It would be helpful to have an explanation of the

Difference Between Grammar And Generative Grammar
GRAMMAR Grammar was considered as one of the most important for the development of a
language. It was defined as set of rules and regulations for English language. There are many
different types of grammar and they are, Comparative Grammar : Comparative grammar was
defined as the analysis and comparison of the grammatical structures of a language. Contemporary
work in comparative grammar was concerned with "a faculty of language that provides an
explanatory basis for how a human being can acquire a first language. In this way, the theory of
grammar was a theory of human language and hence establishes the relationship among all
languages". Generative Grammar The rules determining the structure and interpretation of sentences
that speakers accept as belonging to the language. "Simply put, a generative grammar is a theory of
competence: a model of the psychological system of unconscious knowledge that underlies a
speaker's ability to produce and interpret utterances in a language". Mental Grammar The generative
grammar stored in the brain that allows a speaker to produce language that other speakers can
understand. "All humans are born with the capacity for constructing a Mental Grammar, given
linguistic ... Show more content on Helpwriting.net ...
The verb has eight simultaneous features: moods, kind, type, forms, number, person, tense,
conjunction. There are five moods: indicating, imperative, optative, subjunctive and infinitive. There
are three kinds of actives, middle, and passive: active'I strike': passive 'I am struck' the middle
expression both activity and passitivity, the active is clearly distinct in form the middle/passive; the
middle/passive are distinct formally only in some form,'I was myself'. I do it for myself. There are
three forms, simple compared and derivative (formed from a compound: the "derived" type is
formed from a simple form for

How Psychology Helps Us Understand the Concept of Language...
How Psychology Helps Us Understand the Concept of Language and Intelligence as Related to
Human Beings
Psychology, the study of behaviour and mental processes concerns itself with the reasons organisms
do what they do and how they behave in a particular way, For example why acquired skills are not
lost when learnt ; Why do children rebel against parents and, why humans speak, love and fight each
other. These examples of learning and behaviour are directly related to intelligence and language in
human beings.
It is said that language, foresight, musical skills and other hallmarks of intelligence are connected
through an underlying facility that enhances rapid movements. To most observers, the essence of
Intelligence is ... Show more content on Helpwriting.net ...
Alfred Binet and Theodore Simon together developed a test called the ( Simon Binet Test ), to assess
the ability of children's performance at school. They developed a table used to compare the mental
age of a child to the actual age to produce the concept of I.Q. The conclusion was that a particular
intelligent person often seem quick and capable of juggling many ideas at once.
Not to be outdone, Wechler developed intelligence scales for both adults and children (WAIS &
WISC). The scales are in two parts VERBAL AND PERFORMANCE, giving a clear picture of the
person's IQ; by identifying their strength and weaknesses in specific areas .The information can be
used in planning individualized instruction programs.
To help us understand the nature side of intelligence versus the nurture side Psychologists Bouchard
McGue (1981), and Harrell et al(1955) provided us with correlations and comparisons . In the case
of Bouchard and McGue the correlations thus provided were:
Identical twins reared apart .72
Identical twins reared together .86 compared to
Non–identical twins reared together .60
Siblings reared apart .47
Then child and natural parent .50 while.
Then child and adopted parent .19
These results appear to strongly support the nature issue.

Numerous studies show or emphasizes the influences that environmental factors have on
Intelligence. Harrell et al (1955) compared two groups of enormously

The Importance Of Natural Language In Hamlet In William...
"Something is Rotten in the state of Denmark" (Shakespeare, 1.5.1780) How much power does a
king have? In Early Modern England this question was not one of politics and militaries, but of a
natural social order. The Great Chain of Being Places a King above his country; if the king becomes
corrupted so does the state and in turn, the natural world will become diseased and rank.
Shakespeare's use natural language in hamlet indicates an adherence to The Great Chain of Being.
The corruption of the natural world is a metaphor for the corruption of the state by the perverse
actions of Claudius and Gertrude. These metaphors refer to corrupt animals and plants, to disease
and death, and ultimately connect to the fall of man. Hamlet's ... Show more content on
Helpwriting.net ...
Disease and infection, pungent and potent, is caused by this "Murder most foul" (1.5.1781). This
blight rests upon Claudius and Gertrude, and their sin, disease, and disorder is conferred to
Denmark. As the king and queen of Denmark, Claudius and Gertrude's actions directly influence
their domain. Hamlet reflects the great chain of being in this way, applying the rulers infections and
guilt to Denmark. As Marcellus says, "Something is rotten in the state of Denmark." This statement
is more than an ill portent, but a judgement on a country led by rotten rulers. Like a weeds the sin
overtook the country. Like Gertrude's sexual depravity, "'tis an unweeded garden,/That grows to
seed; things rank and gross in nature" (1.2.1772). These references to environmental corruption
illustrate the decay that results from moral pollution. Claudius and Gertrude's marital bed is already
cursed: as the Ghost says, "So lust, though to a radiant angel linked/Will sate itself in a celestial bed/
and prey on garbage." If the king and the queen are dining on "garbage," the natural world must
follow in turn. Hamlet describes crime and conspiracy in terms of weeds, "Repent what's past, avoid
what is to come/And

Artificial Intelligent, Natural Language Processing
Abstract
We are living in a busy world. Everyone is trying to catchup with almost everything he can. As a
result we all need our own persona assistant to help us out everyday. But not everyone can afford it.
Intelligent Personal
Assistant is the answer for them. Artificial Intelligent is improving fast. And taking advantage of it
in our everyday life can make our life much easier. It can mimic basic things like a human
companion. In this paper we compared between currently popular Intelligent Personal Assistants.
What they can do and what they can not yet. Though they provide state of art features but there is
still many field to make improvement, like improved natural language processing so that we don't
have to use some predefined keyword to get answer.
Chapter 1
Introduction
With the breakthrough of speech recognition, natural language processing, semantic web and
machine learning we can safely say that the age of Intelligent Personal Assistant(IPA) is upon us. A
software agent that can do various task or service for a person is called Intelligent Personal
Assistant.
It depend on user input, location information and various online sources for information about
weather, traffic conditions, news etc. Currently there are many of such agent is available for
everyday use such as Google Now by
Google, Siri by Apple, Amazon Echo, Microsoft Cortana and Facebook's M.
The first fully functional IPA is Denise developed by NextOS formerly known as Guile3D. The
company was founded

State of the Art in Multilingual Text Retrieval Accessing...
In this paper we surveyed the state of the art in multilingual text retrieval accessing parallel web
pages. Multilingual search engines typically consist of a crawler which traverses the web, retrieves
the required web page in the desire languages. It provides front end user interface, which can be
used for selecting language for query submission. The way the query is fired leads into two types of
search Cross–language information retrieval and Multi–language information retrieval. In cross–
language retrieval the user query is machine translated into multiple language queries automatically
as per user selection and then fired. In multi–language retrieval the user has to provide queries in
multiple languages to fetch the web documents in different languages. Also in some search engine
the web page is machine translated and forwarded to the user. NLP is still in the expansion phase
and has to make advances in it, research is going on all over world. Experiment was done with top
rated multilingual search engine to access parallel pages but could not find it. When billions of
parallel web documents are present on the web in different languages why not explore that? A
alternative to that can be searching through parallel pair finder.
Keywords: NLP,MT Machine Translation, CLIR Cross–language, information retrieval,
Multilingual.
1. Introduction
The total number of languages in the world is between 5,000 and 10,000. In a country like India
people speak about 57 different

Semantic Theories Of Natural Language
This essay will discuss semantic theories of natural language. Emphasising on the use of meaning in
language, the process of human thought in language use and also how reality is an influence on
language.
The Oxford Dictionaries(n.d) provide definitions of the key words in enquiry as follows.
("meaning.") " What is meant by a word, text, concept, or action:" .
("thought.")"An idea or opinion produced by thinking, or occurring suddenly in the mind:".
("reality.") "The state of things as they actually exist, as opposed to an idealistic or notional idea of
them: ".
It can be understood that the human language consists of words as spoken or in text as a concept or
to define an action to correlate meaning.
With the words that are chosen to be ... Show more content on Helpwriting.net ...
David Hornsby (2007) claims "we have a mental dictionary or lexicon which stores the form of a
lexeme". Hornsby 's claim is correct as in (??) Noam Chomsky brought forward the idea of a
"Language Acquisition Device".
Language is consistent among the reality shared among speakers rather than a surreal understanding
of the world.
Identifying the meaning of our expressions on the basis of its truth conditions was introduced by
David Donaldson (1967) with a theory of truth–conditional semantics. It aims to define the
semantics of natural language. Davidson expressed the idea that "language expresses meaning to be
true if it coheres with its truth conditions".
Include claims about truth conditional semantics
The truth–conditional theory defines meaning in language to be the same as the truth conditions of
the proposition and .
(Donald Davidson **) Claims
DAVIDSON OPPOSES TO DEFINITIONS OF MEANING OF ENTITIES
It has never been proven that language dramatically shapes the way it's speakers think (Pinker, 48).
It can be said that a cognitive component of language is the language of thought that of which all
humans use.
(**DATE) describes that the language of thought is
(Stephen Pinker **)

Slobin claims"There is a process of "thinking for speaking" in which cognition plays a dynamic role
within the framework of linguistic expression:
Dan L. Slobin (??) describes a cognitive process, which he labelled "thinking for speaking" . This is
the kind

Greek Language Essay
A survey on various platforms for Sanskrit and Part–Of–Speech Tagging Methods
Sulabh Bhatt, Parmar Krunal
Department Of Computer Science, Gujarat University
Ahmedabad, India sulabhbhatt@gmail.com parmar.krunal005@gmail.com
Abstract – In this paper we present a Natural language processing for Sanskrit using Different
approaches. Sanskrit is a oldest and considered as the mother of all languages. The Sanskrit, the
world 's ancient language has got a wealthy grammar. The Sanskrit grammar text Ashtadhyayi is
written by Panini (an Indian Sage). Sanskrit is a well suitable language for providing an advanced
artificial intelligence for Computers. Part of Speech (POS) Tagging is the first step in the
development of any NLP Application. A POS Tagger (POST) is a piece of software that reads text in
some language and assigns parts of speech to each word (and other token), such as noun, verb,
adjective, etc.
Keywords – NLP for Sanskrit, Tagset, POS Tagging, HMM, CRF
I. INTRODUCTION
Natural language processing: Natural language is the embodiment of human cognition and human
intelligence. Natural language processing (NLP) is a cross disciplinary field in computer science and
linguistics where a computer can generate and understand human speech. It is the ability of a
computer program to understand human speech as it is spoken. NLP is a component of artificial
intelligence (AI).The development of NLP applications is challenging because computers
traditionally require humans to "speak"

How Internet Slangs Affect language?
We decided to conduct a questionnaire for the use of Internet slangs within the age group ranging
from 14 to 30, which most of the people within this age group is contacting with Internet slangs
most frequently. For the questionnaire, we interviewed one hundred people and student in City
University of Hong Kong, and half of interviewees are boys while the others are girls. The template
of questionnaire is attached as appendix for reference, and the result and data collected are shown as
below. It is expected that the use of Internet slangs among this age group is widely distributed, and
most of them have used Internet slangs. More precisely, it is shown that female has a higher rate of
using Internet slangs than male. It is predicted that girls would like to use more medium to express
their feeling, such as LOL, OMG. It may also due to the demand of shortening the communication
time or error on texting. The acknowledgement of some popular Internet slangs is expected to be
recognized widely by them. However, some of those less frequently used or new Internet slangs may
not be understood by some of them. It is expected that the understanding of Internet slangs will be
increased with the development of Internet slangs or the popularity of that term. The result proved
that texting is the most frequently used medium for Internet slangs, it is possible that the use of
Internet slangs can facilitate the communication. The results also revealed that they seldom use

How Does Language Shape The Way We Think?
Nothing brings people together more than language. As an international student, I noticed that more
often than not, international students tend to befriend those with a common native language. Perhaps
their common language makes it easier for them to communicate since they might not be
comfortable with speaking English. Another possibility would be that sharing a language can also
mean that they share a common way of thinking. Lera Boroditsky, an assistant psychology professor
at Stanford University, wrote the article "How Does Our Language Shape the Way We Think?" to
illustrate to her readers that language, whether it is grammar or just the general logic, does indeed
affect how we think. Boroditsky and research teams in Stanford and MIT collected data from all
over the world. Because of the extensive amount of research and her article's solid structure, I find
Boroditsky's argument easy to follow and understand, therefore quite convincing. She is so
knowledgeable in her area that her arguments and article are solid and build on top of each other like
Tetris tiles. A well–written article can only be achieved by knowing and understanding your material
well.
The main reason that Boroditsky's argument that language shapes our minds is valid is that the
research she did with her teams covers a wide variety of aspects on this topic while still keeping her
article cohesive. The first research Boroditsky introduces to her audience is the research on the
Kuuk Thaayorre, which is an

Description Of Automatic Text Summarization
Automatic Text Summarization Bhavika S. Joshi Pooja N. Mane Atharva College of Engineering
Atharva College of Engineering Department of Computer Science Department of Computer Science
University of Mumbai University of Mumbai Mumbai, India Mumbai, India Email:
bhavika.joshi1994@gmail.com Email: poojamaner2611@gmail.com Kaveri S. Metkari Atharva
College of Engineering Department of Computer Science University of Mumbai Mumbai, India
Email: kaveri.metkari@gmail.com Abstract – Nowadays people want a quick, rapid and concise
review of any given text rather than going through the entire length of the content. In this growing
age of information technology witty huge amount of data being churned every second users for
reliable context that is short and concise over lengthy paragraphs of text. Realizing this need this
project is based on summarizing content in to a more concise yet informative context without losing
the moral premise or the objective for which the text was originally developed. We employ various
data mining algorithms to condense the entire text into a content rich summary document by
extracting the prominent and relevant information outlining the purpose of the entire text. I.

Language And Poverty In The United States
Poverty
According to the U.S. Census Bureau, in the United States in 2006, the poverty rate for all
individuals was 12.3%. For children under the age of 18, the incidence of poverty was 17%, and for
children under the age of 5, the rate as 20.4%. Poverty do not discriminate, is continuous and it work
in patterns. Poverty is the extension to which an individual does without resources. These resources
can consist of financial, emotional, mental, spiritual, physical, support systems, relationships, and
knowledge of hidden rules .The lack of these resources affects the children development in the way
they analyzed and find a solution to real problems. Educators ought to understand how children with
non–financial resources develop the roles of language, the hidden roles, and the systems of support.
Teachers need to understand that ... Show more content on Helpwriting.net ...
The register of language helps children in their early years to develop the language from a limited
use of words, to a casual language (characterized by a 400–800 words vocabulary), and finally to
talk with a formal language (standard sentence syntax and word choice of work and school). These
aspects of language affect the students that live in poverty because they do not have access to formal
register at home. The lack of formal register combined with a lack of vocabulary, the knowledge of
sentence structure or adequate syntax affects the student to develop a good score and do well in
school. Second, the pattern of discourse helps the student to organize the information. In the formal
register, the patterns of discourse help the student to get straight to the point. However, the students
that have not access to formal register, educators become frustrated with the tendency of these

The Natural Language Processing ( Nlp )
INTRODUCTION Natural Language Processing (NLP): NLP is a process in which human makes
communication with machine easily. NLP is related to area of human and computer interaction.
There are many application developed last few years. The very helpful application is that a machine
take instruction by human voice and follow operation on it. NLP are trying to make computer more
reliable that are easier to use by people. So rather than learn a special language of computer
command, people will talk with computer in their own language. 1.1 MAJOR TASK IN NLP [b]:
1.1.1 Automatic Summarization [b]: It work as the summary of a chunk of text. Like, article in
political section in newspaper. 1.1.2: Machine translation [b]: Automatically translate language from
one human to another human. 1.1.4 Optical Character Recognition [b]: Optical Character
Recognition is a process mechanical or electronic conversion of scanned or photographic image of
typewritten or printed text into machine encode or computer readable text. 1.1.4 Speech recognition
[b]: In speech recognition take a sound clip of the person and determine the textual representation of
speech. 1.1.5 Speech segmentation [b]: In speech segmentation take a sound clip on the person and
separate into words. 1.1.6 Word segmentation [b]: Word segmentation takes the chunk of continuous
text and separate words. 1.2 APPLICATION OF NLP [b]: Classify text into categories Index and
search large text Question answering Speech

Multi Label Semantic Relation Classification
Multi–label Semantic Relation Classification
Between Pair of Nominals
Kartik Dhiwar,
PG Scholar, Department of Computer Science and Engineering, SSGI, SSTC, Bhilai (CG), India
kartikdhiwar21@gmail.com Abhishek Kumar Dewangan
Professor, Department of Computer Science and Engineering, SSGI, SSTC, Bhilai (CG), India
abhishek.dew2006@gmail.com Abstract: Relation classification is a keynote in the field of Natu–ral
Language Processing (NLP) to mine information from text facing problems of over–reliance on the
standard of handcrafted features. Features annotated by specialists and lin–guistic data derived from
linguistic analysis modules is expen–sive and ends up with the difficulty of error propagation. Rela–
tion extraction plays a crucial role in extracting struc–tured data from unstructured sources like raw
text. One might want to seek out interactions between medicines to create medical information or
extract relationships among people to create a simply searchable knowledgebase. We propose a deep
Convolutional Neural Network model for the multi–label text relation classification task without
hand crafted features. This model outperforms the best existing model as per our knowledge without
depending much on manually engineered features with the small updates in the loss function
applied.
Index Terms – Relation Classification, Features, Label, Convolutional Neural Network, Information
Extraction.
.
1. INTRODUCTION
Natural Language Processing tasks are now applicable to

Research Methodology on Natural Language Processing
Research methodology on Natural Language Processing:
The main aim of this project is to research on the integration of "Natural Language Processing " and
information systems engineering to enhance query retrieval in natural language processing.
Defining a research methodology:
The definition of research methodology includes two parts:
– Research definition
– Methodology
Research:
It is defined as a thorough and organized query or investigation on a particular theme to revise or
determine the facts, theories, applications and so on.
Methodology:
It is a system of methods followed by a particular discipline. Thus, research methodology is the way
how a researcher performs research.
Uses of research methodology:
There are many ... Show more content on Helpwriting.net ...
[Gordhan Marshall, 1998]
Objective–1:
To study the concept of natural language processing and various features involved in it.
The above objective is fulfilled by initiating an exact design required for performing the research
process. The research design illustrates the basic understanding about the research (NLP) and
various features.
Research strategies:
Normally, research methodology includes two strategies for performing research.
– Qualitative research
– Quantitative research
Quantitative research:
Quantitative research methods are utilized to study the natural phenomena. So, it includes survey
methods, formal methods, and numerical methods.
Qualitative research:
Qualitative research methods are utilized to study the social and cultural phenomena. So it includes
observation, participant observation (field work), interview sessions, documents and texts and
finally the researcher's imitations and feedback. [Myers, 2009]

Qualitative research is a technique of promoting research that stresses the quality according to the
user's point of view and approaches. In depth interviews and focus groups are best examples of
qualitative research. [Laura Lake, 2009]
Objective–2:
To study various procedures involved in query evaluation of natural language processing
The above objective of the project is fulfilled by selecting a suitable strategy among all the available
strategies. In this research methodology, the researcher used

Dynamic News Classification Using Machine Learning
Dynamic News Classification using Machine Learning Introduction Why this classification is
needed ? (Ashutosh) The exponential growth of the data may lead us to a time in future where huge
amount of data would not be able to be managed easily. Text Classification is done through Text
Mining study which would help sorting the important texts from the content or a document to
manage the data or information easily. //Give a scenario, where classification would be mandatory.
Advantages of classification of news articles (Ayush) Data classification is all about tagging the data
so that it can be found quickly and efficiently.The amount of disorder data is increasing at an
exponential rate, so if we can build a machine model which can automatically classify data then we
can save time and huge amount of human resources. What you have done in this paper (all) Related
work In this paper [1] , the author has classified online news article using Term Frequency–Inverse
Document Frequency (TF–IDF) algorithm.12,000 articles were gathered & 53 persons were to
manually group the articles on its topics. Computer took 151 hours to implement the whole
procedure completely and it was done using Java Programming Language.The accuracy of this
classifier was 98.3 % . The disadvantages of using this classifier was it took a lot of time due to
large number of words in the dictionary. Sometimes the text contained a lot of words that described
another category since the

Text Analysis : Text Mining
Text mining sometimes known as text data mining often refers to the process of pulling out of
interesting and non–trivial patterns of knowledge form a semi or unstructured text document. Text
mining can also serve as an extension of data mining or of data finding from a structures database.
With text mining it can be the same as data mining but with a bit more complexity, because they
somewhat carry out the same processes and has the same purpose, however with text mining the
data is more unstructured rather that structured in the data files such as : (pdf, word, xml etc.). This
is so because most people store information in the form of text, it is believed that text mining can be
greater than data mining, during recent years there where a number of studies done which indicates
that 80% of business information is stored in text format.
Text mining is an interdisciplinary field which involved retrieving information, text analysis,
information extraction, clustering, categorization, visualizations, database technology, machine
learning and data mining.
Text mining can be of great help to different area where there are large amount of data/ information
such as accounting( monthly reports),human resource(employee reports),marketing(customer
feedback) just to name a few . With text mining we don't just use it as a means of filter but it can
also be used for prioritizing emails based on their level of important
Differentiate between text mining, text analytics and data

Questions On Natural Language Processing

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