This paper proposes methods to determine the box office performance of movies using cloud computing and social media. It introduces the UIB algorithm which uses IMDB via a web browser to lookup performance but requires significant time. The AAF algorithm leverages social networks like Facebook by posting status updates but provides lower accuracy. A hybrid AAFtUIB approach is presented that asks friends to use IMDB, providing high accuracy with minimal effort. The paper also discusses implementing the algorithms and relates them to prior work.

1. Use Of Cloud-Computing And Social Media To Determine Box Office Performance
USE OF CLOUD-COMPUTING AND SOCIAL MEDIA TO
DETERMINE BOX OFFICE PERFORMANCE
1
RIAA SETH, 2BALDEV SINGH
1
Student at Sokal Insititute of Technology, Pune, 2Lecturer at Sokal Institute of Technology, Pune
Email: riaaseth@gmail.com, baldev.thakur@yahoo.com
Abstract— Determining the box-office performance of a movie remains one of the most challenging grand problems posed
by Hilbert. It has not only theoretical implications, but the commercial value of a solution would also be tremendous. In
this paper we show that this problem can be solved to a high degree of accuracy through the use of cloud computing
techniques, and the use of social media networks. We also provide a hybrid approach which works the best.
Index Terms—HTTP Protocol, Facebook, Twitter, Internet
I.
this case[18] and can be made embedded, ubiquitous,
and linear-time. Specifically we describe the UIB
algorithm, whose architectural overview is given in
Figure 1.
INTRODUCTION
Interrupts must work. Unfortunately, a typical
quagmire in cyberinformatics is the investigation of
"fuzzy" models. After years of essential research into
web browsers, we argue the deployment of Boolean
logic, which embodies the practical principles of evoting
technology.
The
improvement
of
reinforcement learning would tremendously amplify
Bayesian models. As is clear from the title of this
paper, this paper deals with the entertainment
industry. So, we do provide entertainment in this
paper. So, if you are reading this paper for
entertainment, we suggest a heuristic that will allow
you to read this paper efficiently. You should read
any paragraph that starts with the first 4 words in
bold and italics – those have been written by the
author in painstaking detail. However, if a paragraph
does not start with bold and italics, feel free to skip it
because it is gibberish auto-generated by the good
folks at SCIGen. The rest of the paper proceeds as
follows. In Section 2, we describe our UIB algorithm,
to show how we can use cloud computing
methodologies to get a solution to the box-office
performance determination problem to a high degree
of accuracy, but with a high cost in terms of time
spent. In Section 3, we describe our AAF algorithm,
to show how social networks can be leveraged to
solve the problem with minimal effort. However, the
accuracy of the method is lower. In Section 4, we
propose a hybrid method, AAFtUIB, which gives
highly accurate results with minimal effort. In
Section 5, we use the UIB method to determine the
textual content of a few minutes of one of our
favourite movies. Section 6 is the related work, and
Section 7 contains our conclusions.
II.
Figure 1: The architectural layout used by UIB
Typically, a data center is a facility within a
computing environment that is used to house mission
critical
computer
systems
and
associated
components. A data center includes environmental
controls, such as air conditioning, fire suppression,
and the like, redundant/backup power supplies,
redundant data communications connections and
high security among others. A bank, for example,
may have a data center, where all its customers'
account information is maintained and transactions
involving these data are performed. Likewise, in
another example, practically every company either
mid-sized or larger has some kind of data center with
larger companies often having dozens of data
centers. Besides, most large cities have many
purpose-built data center buildings in secure
locations near telecommunications services. Most
collocation centers and Internet peering points are
located in these kinds of facilities. But the motivated
reader is encouraged to not read too much into the
previous paragraph, because it was copy-pasted from
CLOUD-BASED UIB
Despite Xeno's paradox, we can demonstrate that use
of cloud-computing technologies can be beneficial in
IRAJ International Conference-Proceedings of ICRIEST-AICEEMCS, 29th December 2013, Pune India. ISBN: 978-93-82702-50-4
93

2. Use Of Cloud-Computing And Social Media To Determine Box Office Performance
a random document on the internet. The real key to
the UIB algorithm is this: UIB stands for “Use
IMDB.com via a Browser”and in this method we
simply go to IMDB.com, navigate to the page for the
movie we're interested in and check whether the box
office performance has been listed there. If yes, we
report that number. If not, we try again after a few
days. This is repeated a maximum of 5 times.
III.
Since we are big fans of Jeff Naughton, we have
followed the same approach in this paper, and hence
section 4 contains a hybrid algorithm. The name of
our hybrid algorithm is AAFtUIB, which, if you've
been paying attention stands for Ask a Friend to Use
IMDB.com via a Browser. Obviously this requires
only as much effort as the AAF algorithm, and yet, if
you have any decent friends, it can give accuracy
levels that are the same as UIB.
SOCIAL-MEDIA BASED AAF
V.
Obviously, in spite of the fact that the UIB method
provides very accurage results, it is clear that it
requires too much effort. Here social media comes to
our rescue and we've developed the AAF algorithm.
It is a self-evident truth that Sholay is the best movie
ever made (at least according to the wife of the
author of this paper). Now, if you're paying attention,
the first author of the paper appears to be Riaa Seth,
which would indicate that she cannot have a wife,
because the Supreme Court of India just upheld
Section 377. But, samajhne ki baat yeh hai ki, Riaa
Seth is not really the author of this paper – instead it
is Navin Kabra, whose wife is Meeta Kabra, the
owner of wogma.com. Please visit wogma.com for
great movie reviews, which don't give the movie
away. She is currently reviewing Dhoom 3, and we
predict that she will give it a rating of “Even the
keen, wait for DVD”. But our AAF algorithm
indicates that it will be a box-office hit. Another
problem is that if we indeed insert Sholay dialogues
here, they will all show up in red due to the spell
check, and we are a little worried that someone
might hit pagedown and notice that section. So,
instead we are replacing it with dialogues from our
wife's favorite English movie, My Cousin Vinnie:
Figure 2: Overview of the AAF Algorithm.
Figure 2, which is supposed to given an overview of
the AAF algorithm is simply a random image that
we downloaded off of Google's image search using
the search string “how to use Facebook”. By now you
must clearly be wondering what AAF stands for and
how does it work. The full form of AAF is ask a
friend, and we do that by posting a status update on
Facebook. When someone replies with an answer we
simply note that down. If more than one person gives
an answer, we take an average. Clearly, this method
requires very little work, but has the advantage of
offloading all the work to our friends, while we can
chill and have a beer.
IV.
IMPLEMENTATION
1) Hardware and Software Configuration
HYBRID ALGORITHM – AAFTUIB
Figure 3: The average block size of BonPoser, as a function of
work factor.
One of the top database researchers in the world, Jeff
Naughton had once pointed out that a standard
University of Wisconsin paper consists of section 1
giving a grand introduction, section 2 describing
simple algorithm #1, section 3 describing simple
algorithm #2, and section 4 contains a hybrid of the
two algorithms which outperforms both. This, he
pointed out, is enough for the paper to get accepted.
He: I don't know, he's got a boar, a bear, a couple of
deer.
She: Whoa. You're gonna shoot a deer?
He: I don't know. I suppose. I mean, I'm a man's
man, I could go deer hunting.
She: A sweet, innocent, harmless, leaf-eating, doeeyed little deer.
IRAJ International Conference-Proceedings of ICRIEST-AICEEMCS, 29th December 2013, Pune India. ISBN: 978-93-82702-50-4
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3. Use Of Cloud-Computing And Social Media To Determine Box Office Performance
He: Hey Lisa, I'm not gonna go out there just to
wimp out, you know. I mean, the guy will lose
respect for me, would you rather have that?
[She gets up, walks over to the bathroom and shuts
the door]
He: What about these pants I got on, you think
they're O.K.?
[Looks down]
He: Oh!
She: [comes out of the bathroom] Imagine you're a
deer. You're prancing along, you get thirsty, you spot
a little brook, you put your little deer lips down to the
cool clear water... BAM! A fuckin bullet rips off part
of your head! Your brains are laying on the ground
in little bloody pieces! Now I ask ya. Would you give
a fuck what kind of pants the son of a bitch who shot
you was wearing? Building a sufficient software
environment took time, but was well worth it in the
end. We implemented our Scheme server in Scheme,
augmented with computationally noisy extensions
[23]. Our experiments soon proved that refactoring
our 802.11 mesh networks was more effective than
microkernelizing them, as previous work suggested.
Further, we implemented our the transistor server in
ANSI Prolog, augmented with mutually wireless
extensions. All of these techniques are of interesting
historical significance; H. White and C. Bose
investigated an orthogonal heuristic in 1977. We
first analyze experiments (1) and (4) enumerated
above
as
shown
in
Figure 4.
Gaussian
electromagnetic disturbances in our Internet-2 cluster
caused unstable experimental results. Continuing
with this rationale, the data in Figure 4, in
particular, proves that four years of hard work were
wasted on this project. Similarly, the curve in
Figure 4 should look familiar; it is better known as
F(n)
=
n.
We next turn to experiments (1) and (3) enumerated
above, shown in Figure 4. Note that linked lists have
smoother flash-memory speed curves than do
microkernelized DHTs. The curve in Figure 5 should
look familiar; it is better known as G−1(n) = n. On a
similar note, of course, all sensitive data was
anonymized during our bioware deployment. Lastly,
but not the leastly, my friend Shrikant, who is likely
to read this paper will never forgive me if I don't
mention in this paper that the answer to the ultimate
question of life, the universe and everything is 42.
VI.
we simulate only essential epistemologies in
BonPoser. We had our solution in mind before White
and Sun published the recent famous work on virtual
configurations [22,3]. Furthermore, Martinez et al.
[6] developed a similar solution, unfortunately we
disconfirmed that our algorithm follows a Zipf-like
distribution. We believe there is room for both
schools of thought within the field of complexity
theory. The original solution to this obstacle by
Kobayashi [6] was considered practical; nevertheless,
such a hypothesis did not completely achieve this
objective. The only other noteworthy work in this
area suffers from fair assumptions about the
simulation of expert systems. We plan to adopt many
of the ideas from this prior work in future versions of
our framework. A number of existing heuristics have
visualized systems, either for the analysis of
superblocks [10] or for the simulation of DHTs that
would allow for further study into SCSI disks. Thus,
comparisons to this work are unfair. The choice of
the transistor in [8] differs from ours in that we
construct only key archetypes in BonPoser [16].
White [19,2] developed a similar framework,
contrarily we demonstrated that our methodology is
recursively enumerable [9]. All of these methods
conflict with our assumption that "smart"
epistemologies and write-back caches are technical
[15]. Therefore, comparisons to this work are illconceived. Our solution is related to research into
autonomous theory, forward-error correction, and
digital-to-analog converters [10,1,13]. Complexity
aside, BonPoser studies more accurately. Suzuki et
al. [17] suggested a scheme for architecting the
partition table [23], but did not fully realize the
implications of the location-identity split at the time.
Lee et al. [24,5,18] and Johnson introduced the first
known instance of write-ahead logging [21]. We had
our method in mind before White and Jackson
published the recent infamous work on knowledgebased communication [14,12,11].
CONCLUSION
In this position paper we described UIB, a method to
use the browser to check IMDB.com to lookup box
office performance of movies, and AAF, a method to
ask friends on Facebook about how a movie is doing,
and a hybrid algorithm AAFtUIB in which we ask a
friend to use IMDB.com. And we've managed to
reference Hilbert, HHGTTG, Sholay, My Cousin
Vinny, Jeff Naughton, the Wisconsin Database
Performance Paper, Xeno's paradox, Meeta Kabra
and the wogma.com website, and we even referenced
the Sokal Affair in the heading of the paper (actually
in the name of the institute that the authors are from,
but you get what I mean, right?) proving once and
for all that nobody has read this paper. AAFtUIB
will address many of the issues faced by today's
RELATED WORK
A number of prior systems have constructed
multimodal theory, either for the understanding of
massive multiplayer online role-playing games that
would allow for further study into reinforcement
learning or for the visualization of RPCs. This is
arguably ill-conceived. Along these same lines, the
choice of SCSI disks in [20] differs from ours in that
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4. Use Of Cloud-Computing And Social Media To Determine Box Office Performance
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set a precedent for interposable archetypes, and we
expect that computational biologists will study
BonPoser for years to come. In fact, the main
contribution of our work is that we confirmed that
access points [18] and superpages [26] can
collaborate to solve this quagmire. Finally, we
motivated a constant-time tool for developing RPCs
(AAFtUIB), confirming that multicast algorithms
can be made homogeneous, probabilistic, and
reliable.
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