OneCompiler

latex all

1985
  1. Develop a LaTeX script to create a simple document that consists of 2 sections
    [Section1, Section2], and a paragraph with dummy text in each section. And also
    include header [title of document] and footer [institute name, page number] in the
    document.
    //program1.tex
    \documentclass{article}
    \usepackage{authoraftertitle}
    \usepackage{fancyhdr}
    \fancyhead{}
    \fancyhead[L]{left header}
    \fancyhead[R]{right header \quad \thepage}
    \fancyfoot{}
    \fancypagestyle{plain}{
    \fancyhead{}
    \fancyhead[C]{Intent based Search Diversification}
    \fancyfoot{}
    \fancyfoot[C]{VKIT, Bangalore}
    }
    \pagestyle{fancy}
    \title{Search Optimization Process}
    \begin{document}
    \maketitle
    \section{Context based Diversification}
    The human era is evolved and dominated through the ultimate intention to know
    about the Universe and its assets more and more. This in turn persuaded him to gather
    the immense information of need in the form of theory, tools, intuitions, visuals, and
    ultimately as the form of abstract objects.
    \section{ Conceptualization of the Search Queries}
    Deciding the context of the search query based on its representation over a concept
    network using fuzzy methods provides a better thrust to the overall search process.
    The existing context based search diversification process emphasizes the importance
    of the numerical representation of the query over a data repository. The search
    operation can use these semantically meaningful segments as a confident segment in
    the conceptual network.
    \end{document}
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    //Output
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  2. Develop a LaTeX script to create a document that displays the sample
    Abstract/Summary
    //program2.tex
    \documentclass{article}
    \usepackage{ragged2e}
    \title{\textbf{Abstract}}
    \vspace{-8ex}
    \date{}
    \begin{document}
    \maketitle
    \thispagestyle{empty}
    \justify{Whenever multi-sense or non-domain specificity
    arises in a query it is difficult to deliver exact or approximate
    results to users for that query in considerable time limit. Modern
    search engines fetch enough similar results for a query over
    a data tree or a corpus by applying query approximation
    algorithms. The proposed approximate query answering model
    called Query Answering with Pointed Graphs (QAPG) achieves
    query approximation by evaluating the user concerned queries
    on proper semantic paths on an Accessible Pointed Graph (APG)
    relaxed with architectural clues.}
    \vspace{1mm}
    \justify{The proposed model formulates semantically
    inferred path algebra for a query and performs the path mapping
    with other set of path algebras of corresponding query keywords
    or a closely matched fuzzy set of another corresponding query
    keywords to find approximate queries. The concept of APG is
    used for weaving the paths, subsumed with the given concerned
    keyword set. Users are more concerned about their choice of
    search context so each selected attribute of the query is weighted
    according to the nature of data items either numerical or
    categorical in type.}
    \vspace{1mm}
    \justify{The content similarity function is used to
    associate the categorical values to weighted attributes to evaluate
    overall content similarity. The overall similarity of the obtained paths is calculated
    from the association of content similarity and twig level similarity. The approximation
    function elegantly
    combines structure with contents to answer approximate queries.
    User preference on top-k answers are adjusted by an adjustment
    coefficient. The approximation function can find out a range of
    most relevant answers from a large number of XML data sources
    by tuning the adjustment coefficient.}
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    \justify{\textbf{Keywords:} Path algebra, Twig, APG, Architectural clues, Content
    similarity.}
    \end{document}
    //Output:
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  3. Develop a LaTeX script to create a simple title page of the VTU project
    Report [Use suitable Logos and text formatting]
    //program3.tex
    \documentclass[a4paper, 12pt]{report}
    \usepackage{graphicx}
    \usepackage{xcolor}
    \begin{document}
    \include{FrontPage-VTU}
    \end{document}
    //FrontPage-VTU.tex
    \thispagestyle{empty}
    \pagenumbering{roman}
    \setcounter{page}{1}
    \begin{center}
    \textbf{\large Intent based Diversification of Query Keywords}
    \end{center}
    \vspace{18mm}
    \begin{center}
    \begin{small}
    A Project Report\
    Submitted for the Award of the Degree\
    of\
    Bachelor of Engineering\
    in\
    Computer Science and Engineering\
    by\
    \vspace{.5cm}
    \textbf{Komalavalli P}\
    IV SEM\
    \vspace{.3cm}
    Under the guidance of\
    \vspace{.5cm}
    \textbf{Dr. Vidya A}\
    Professor, HoD\
    Vivekananda Institute of Technology\
    Visvesvaraya Technological University, Belgavi.\
    \end{small}
    \vspace{10mm}
    \centerline{\includegraphics[scale=.4]{vtu1}}
    \vspace{20mm}
    Department of Computer Science and Engineering\
    Vivekananda Institute of Technology,\
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    Visvesvaraya Technological University, Belgavi.\
    \color{white}jg\color{black}\
    April 2024\
    \end{center}
    //Output
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  4. Develop a LaTeX script to create the Certificate Page of the Report [Use
    suitable commands to leave the blank spaces for user entry]
    //program4.tex
    \documentclass[a4paper, 12pt]{report}
    \usepackage{graphicx}
    \usepackage{ragged2e}
    \usepackage{xcolor}
    \begin{document}
    \include{Certificate-VTU}
    \end{document}
    //Certificate-VTU.tex
    \thispagestyle{empty}
    \pagenumbering{roman}
    \setcounter{page}{1}
    \begin{center}
    \textbf{\large Visvesvarya Technological University}\newline
    \textbf{\small JnanaSangama BELAGAVI - 590018}
    \newline
    \newline
    \centerline{\includegraphics[scale=.4]{vtu1}}
    \newline
    \newline
    \textbf{\small DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING}
    \newline
    \newline
    \textbf{\large CERTIFICATE}
    \end{center}
    \vspace{5mm}
    \justify{This is to certify that Mr. Basvaraju K N bearing USN:1VKIT20CS008 is a
    bonafide student of Bachelor of Engineering course of the Department of Computer
    Science and Engineering, VTU, Belgavi, affiliated to Visvesvaray Technological
    University, Belagavi. Project report on "Context-based Diversication of Search
    Engines" is prepared by him under the guidance of Dr. Haneefa Shafi in partial
    fulfillment of the requirements for the award of the degree of Bachelor of Engineering
    of Visvesvaray Technological University, Belagavi, Karnataka.}
    \newline
    \newline
    \newline
    ............................ \hspace{16mm} .............................\hspace{16mm}.........................
    \newline
    \newline
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    Dr. Haneefa Shafi \hspace{16mm} Dr. Sangeetha P \hspace{14mm} Dr. Kuriyan M
    A
    \newline
    \newline
    Signature of Guide \hspace{13mm} Signature of HoD \hspace{11mm} Signature of
    Principal
    \begin{center}
    \vspace{10mm}
    \textbf{\small EXTERNAL EXAMINER}
    \end{center}
    \vspace{5mm}
    Name of Examiners \hspace{60mm} Signature with date
    \newline
    \newline

\newline
\newline
2.
//Output
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4. Develop a LaTeX script to create a document that contains the following table
with proper labels.
//program5.tex
\documentclass{article}
\usepackage[utf8]{inputenc}
\begin{document}
\begin{tabular}{|c|c|c|c|c|c|}
\hline
Sl.NoSl.No & USNUSN& StudentnameStudent name &\multicolumn{3}{c|}{Marks}\
\cline{4-6}
& & & Subject1 & Subject2 &Subject3 \ \hline
1& 4XX22XX001&Name1 &89 &60 &90 \ \hline
2& 4XX22XX002&Name2 &78 &45 &98 \ \hline
3& 4XX22XX003&Name3 &67 &55 &59 \ \hline
\end{tabular}
\end{document}
//Output
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5. Develop a LaTeX script to include the side-by-side graphics/pictures/figures
in the document by using the subgraph concept
//program6.tex
\documentclass{standalone}
\usepackage{tikz}
\usetikzlibrary{graphs.standard}
\begin{document}
\begin{tikzpicture}
\graph[nodes={circle,draw},simple]
{
subgraph K_n [n=8,clockwise];
};
\end{tikzpicture}
\begin{tikzpicture}
\graph[nodes={circle,draw},simple]
{
subgraph K_n [n=8, clockwise] -> mid;
};
\end{tikzpicture}
\begin{tikzpicture}
\graph[nodes={circle,draw},simple]
{
subgraph K_n [n=8,clockwise];
8 -!- 3 -!- 4 -!- 5 -!- 2;
};
\end{tikzpicture}
\end{document}
//Output
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6. Develop a LaTeX script to create a document that consists of the following
two mathematical equations
//program7.tex
\documentclass[a4paper, 12pt]{report}
\usepackage{esvect}
\usepackage{amsmath,amssymb,amsfonts}
\usepackage{ragged2e}
\begin{document}
\begin{equation*}
\begin{split}
x=\frac{-b \pm \sqrt{b\textsuperscript{2}-4ac}}{2a}
\end{split}
\end{equation*}
\begin{equation*}
\begin{split}
=\frac{-2 \pm \sqrt{2\textsuperscript{2}-41(-8)}}{21}
\end{split}
\end{equation}
\begin{equation*}
\begin{split}
=\frac{-2 \pm \sqrt{4+32}}{2}
\end{split}
\end{equation*}
\begin{equation*}
\begin{split}
\partial
\textsuperscript{λ\lambda}\textsubscript{σ\sigma}A\textsubscript{t}=\sum
\textsubscript{π\pi in C\textsubscript{t}} sgn(\pi) \partial
\textsuperscript{λ\lambda}\textsubscript{σ\sigma} \partial
\textsuperscript{λ\lambda}\textsubscript{π\pi}
\end{split}
\end{equation*}
\begin{equation*}
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\begin{split}
=\sum \textsubscript{τ\tau in C\textsubscript{σ\sigmat}}
sgn(\sigma\textsuperscript{-1}\tau\sigma) \partial
\textsuperscript{λ\lambda}\textsubscript{σ\sigma}\partial
\textsuperscript{λ\lambda}\textsubscript{σ\sigma\textsuperscript{-1}τ\tau
σ\sigma}
\end{split}
\end{equation*}
\begin{equation*}
\begin{split}
=A\textsubscript{σ\sigmat ∂\partial
\textsuperscript{λ\lambda}\textsubscript{σ\sigma}}
\end{split}
\end{equation*}
\end{document}
//Output:
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7. Develop a LaTeX script to demonstrate the presentation of Numbered
theorems, definitions, corollaries, and lemmas in the document
//program8.tex
\documentclass{article}
\usepackage[english]{babel}
\usepackage{ragged2e}
\newtheorem{theorem}{Theorem}
\newtheorem{corollary}{Corollary}[theorem]
\newtheorem{lemma}[theorem]{Lemma}
\newtheorem{definition}{Definition}[section]
\begin{document}
\section{Theorem}
\begin{theorem}[Accessible pointed graph]
\justify{Consider an XML database D and a twig query q with only ancestor,
descendant relationships in branching edges. The worst case I/O complexity is
decided by the number of holistic nodes in the path algebra. The above theorem
strongly supports the existence of accessible pointed graphs in a tree.}
\end{theorem}
\section{Corollary}
\begin{corollary}
Corresponding corollary
\end{corollary}
\section{Lemma}
\begin{lemma}
Corresponding Lemma
\end{lemma}
\section{Definition}
\begin{definition}
Corresponding definition
\end{definition}
\end{document}
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//Output:
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8. Develop a LaTeX script to create a document that consists of two paragraphs with a
minimum of 10 citations in it and display the reference in the section.
//program9.tex
\documentclass[a4paper, 12pt]{report}
\thispagestyle{plain}
\begin{document}
\thispagestyle{empty}
\pagenumbering{arabic}
\setcounter{page}{1}
\chapter{Search Process on Fly}
\section{Context based Diversification}
The human era is evolved and dominated through the ultimate intention to know
about the Universe and its assets more and more. This in turn persuaded him to gather
the immense information of need in the form of theory, tools, intuitions, visuals, and
ultimately as the form of abstract objects \cite{ffy}, \cite{xyshw}, \cite{tbhs},
\cite{dpgk}, \cite{jaip}, \cite{pdkgvym}.
Deciding the context of the search query based on its representation over a concept
network using fuzzy methods provides a better thrust to the overall search process.
The existing context based search diversification process emphasizes the importance
of the numerical representation of the query over a data repository \cite{fpsu},
\cite{sysxh}, \cite{zwjfw}, \cite{dwhh}. The search operation can use these
semantically meaningful segments as a confident segment in the conceptual network.
\bibliographystyle{IEEEtran}
\bibliography{prg9}
\end{document}
//prg9.bib
@article{ffy,
author={Liu, Fei and Liu, Feifan and Liu, Yang},
title={{A Supervised Framework for Keyword Extraction from Meeting
Transcripts}},
journal={IEEE Transactions on Audio, Speech, and Language Processing},
publisher={IEEE},
volume={19},
number={3},
pages={538-548},
year={2011}
}
@article{xyshw,
author={Liu, Xueqing and Song, Yangqiu and Liu, Shixia and Wang, Haixun},
title={{Automatic Taxonomy Construction from Keywords}},
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journal={Proceedings of the 18th ACM SIGKDD international conference on
Knowledge discovery and data mining},
organization={ACM},
pages={1433-1441},
year={2012}
}
@article{pdkgvym,
author={Papadimitriou, Dimitra and Koutrika, Georgia and Velegrakis, Yannis and
Mylopoulos, John},
title={{Finding Related Forum Posts through Content Similarity over Intention-
based Segmentation}},
journal={IEEE Transactions on Knowledge and Data Engineering},
publisher={IEEE},
volume={29},
number={9},
pages={1860-1873},
year={2017}
}
@article{jaip,
author={Jain, Alpa and Ipeirotis, Panagiotis G},
title={{A Quality-Aware Optimizer for Information Extraction}},
journal={ACM Transactions on Database Systems},
publisher={ACM New York, NY, USA},
volume={34},
number={1},
pages={1-48},
year={2009}
}
@article{dpgk,
author={Papadimitriou, Dimitra and Koutrika, Georgia and Velegrakis, Yannis and
Mylopoulos, John},
title={{Finding Related Forum Posts through Content Similarity over Intention-
based Segmentation}},
journal={IEEE Transactions on Knowledge and Data Engineering},
publisher={IEEE},
volume={29},
number={9},
pages={1860-1873},
year={2017}
}
@article{tbhs,
author={Chien, Jen-Tzung and Chueh, Chuang-Hua},
title={{Topic-based Hierarchical Segmentation}},
journal={IEEE Transactions on Audio, Speech, and Language Processing},
publisher={IEEE},
volume={20},
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number={1},
pages={55-66},
year={2011}
}
@article{fpsu,
author={Ferragina, Paolo and Scaiella, Ugo},
title={{Tagme: On-the-Fly Annotation of Short Text Fragments}},
journal={Proceedings of the 19th ACM international conference on Information and
knowledge management},
publisher={ACM},
pages={1625-1628},
year={2010}
}
@article{sysxh,
author={Song, Yangqiu and Liu, Shixia and Liu, Xueqing and Wang, Haixun},
title={{Automatic Taxonomy Construction from Keywords via Scalable Bayesian
Rose Trees}},
journal={IEEE Transactions on Knowledge and Data Engineering},
publisher={IEEE},
volume={27},
number={7},
pages={1861-1874},
year={2015}
}
@article{zwjfw,
author={Zhuang, Yueting and Wang, Hanqi and Xiao, Jun and Wu, Fei and Yang,
Yi and Lu, Weiming and Zhang, Zhongfei},
title={{Bag-of-Discriminative-Words Representation via Topic Modeling}},
journal={IEEE transactions on knowledge and data engineering},
publisher={IEEE},
volume={29},
number={5},
pages={977-990},
year={2017}
}
@article{jwjh,
author={Shen, Wei and Wang, Jianyong and Han, Jiawei},
title={{Entity Linking with a Knowledge Base: Issues, Techniques, and Solutions}},
journal={IEEE Transactions on Knowledge and Data Engineering},
publisher={IEEE},
volume={27},
number={2},
pages={443-460},
year={2015}
}
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@article{dwhh,
author={Dou, Dejing and Wang, Hao and Liu, Haishan},
title={{Semantic Data Mining: A Survey of Ontology-based Approaches}},
journal={Proceedings of the 2015 IEEE 9th international conference on semantic
computing (IEEE ICSC 2015)},
organization={IEEE},
pages={244-251},
year={2015}
}
//output
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9. Develop a LaTeX script to design a simple tree diagram or hierarchical structure
in the document with appropriate labels using the Tikz library.
//program10.tex
\documentclass{standalone}
\usepackage{tikz}
\usetikzlibrary{graphs.standard}
\begin{document}
\begin{tikzpicture}
[level distance=10mm,
every node/.style={fill=blue!40,circle,inner sep=1pt},
level 1/.style={sibling distance=20mm,nodes={fill=blue!40}},
level 2/.style={sibling distance=10mm,nodes={fill=blue!40}},
level 3/.style={sibling distance=5mm,nodes={fill=blue!40}}]
\node {50}
child {node {40}
child {node {10}
}
child {node {12}
}
}
child {node {60}
child {node {19}
child {node {11}
}
}
child {node {18}}
};
\end{tikzpicture}
\end{document}
//output:
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10. Develop a LaTeX script to present an algorithm in the document using
algorithm/algorithmic/algorithm2e library.
//program11
\documentclass{article}
\newcommand{\que}{\mathord{?}}
\usepackage{algorithm, algpseudocode}
\pagestyle{plain}
\title{Algorithm to find a number is positive or negative}
\date{}
\begin{document}
\maketitle
\begin{algorithm}[H]
\caption{Algorithm to check the sign of a number}\label{euclid}
\begin{algorithmic}[1]
\Procedure{}{}\newline
\textbf{Input:} Read the number from user console\newline
\textbf{Output:} Display the sign of the given number\newline
\State{Read the number num}
\State{if num >> zero}
\State{num is positive}
\State{else if num<< zero}
\State{num is negative}
\State{else num is zero}
\EndProcedure
\end{algorithmic}
\label{alg_1}
\end{algorithm}
\end{document}
//output
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11. Develop a LaTeX script to create a simple report and article by using suitable
commands and formats of user choice.
//program12.tex
\documentclass[a4paper, 12pt]{report}
\usepackage{graphicx}
\usepackage{ragged2e}
\usepackage{xcolor}
\begin{document}
\include{FrontPage-VTU}
\include{Certificate-VTU}
\tableofcontents
%\pagenumbering{arabic}
%\setcounter{page}{1}
\thispagestyle{empty}
\chapter{Introduction}
\pagenumbering{arabic}
\setcounter{page}{1}
\section{Context based Diversification}
The human era is evolved and dominated through the ultimate intention to know
about the Universe and its assets more and more. This in turn persuaded him to gather
the immense information of need in the form of theory, tools, intuitions, visuals, and
ultimately as the form of abstract objects \cite{ffy}, \cite{xyshw}, \cite{tbhs},
\cite{dpgk}, \cite{jaip}, \cite{pdkgvym}.
Deciding the context of the search query based on its representation over a concept
network using fuzzy methods provides a better thrust to the overall search process.
The existing context based search diversification process emphasizes the importance
of the numerical representation of the query over a data repository \cite{fpsu},
\cite{sysxh}, \cite{zwjfw}, \cite{dwhh}. The search operation can use these
semantically meaningful segments as a confident segment in the conceptual network.
\chapter{Literature Review}
Corresponding Literature works
\chapter{Methodology}
Corresponding Methodology
\chapter{Performance analysis}
Corresponding Performance analysis
\renewcommand{\thefigure}{4.1}
\begin{figure}[htbp]
\centerline{\includegraphics[scale=.8]{CN}}
\caption{A portion of concept network for query "hotel California".}
\label{fig}
\end{figure}
\chapter{Conclusion}
Corresponding Conclusion
\bibliographystyle{IEEEtran}
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\bibliography{prg9}
\end{document}
//Output:
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