Arthouse Convergence Presentation: Branding, San Rafael July 2014Tim League
I gave this presentation at the West Coast Arthouse Convergence Regional Conference in San Rafael on July 10, 2014. The topic was "Building Your Brand." The program description was as follows:
"Building a cohesive brand for your theater that incorporates the unique qualities of your community can be daunting. How do you ensure consistency? What should be the message behind your brand? What does a “brand” even mean? Join us as we explore the national, regional and local branding that our cinemas deploy as we root ourselves in our communities."
Not sure why there are boxes around the logos in the SlideShare version. Ironic that in a show about brand, I violate brand standards with said boxes. They don't appear on the presentation version...
The amount of digital data in the new era has grown exponentially in recent years and with the development of new technologies, is growing more rapidly than ever before.
Nevertheless, simply knowing that all these data are out there is easily understandable, utilizing these data to turn a profit is not trivial.
The need of data mining techniques able to extract profitable insight information is the next frontier of innovation, competition and profit.
A data analytic services provider, in order to well-scale and exponentially grow its profit, has to deal with scalability, multi-tenancy and self-adaptability.
In big data applications, machine learning is a very powerful instrument but a bad choice regarding the algorithm and its configuration parameters can easily lead to poor results. The key problem is automating the tuning process without a priori knowledge of the data and without human intervention.
In this research project we implemented and analysed TunUp: A Distributed Cloud-based Genetic Evolutionary Tuning for Data Clustering.
The proposed solution automatically evaluates and tunes data clustering algorithms, so that big data services can self-adapt and scale in a cost-efficient manner.
For our experiments, we considered k-means as clustering algorithm, that is a simple but popular algorithm, widely used in many data mining applications.
Clustering outputs are evaluated using four internal techniques: AIC, Dunn, Davies-Bouldin and Silhouette and an external evaluation: AdjustedRand.
We then performed a correlation t-test in order to validate and benchmark our internal techniques against AdjustedRand.
Defined the best evaluation criteria, the main challenge of k-means is setting the right value of k, that represents the number of clusters, and the distance measure used to compute distances of each pair of points in the data space.
To address this problem we propose an implementation of the Genetic Evolutionary Algorithm that heuristically finds out an optimal configuration of our clustering algorithm.
In order to improve performances, we implemented a parallel version of genetic algorithm developing a REST API and deploying several instances in the Amazon Cloud Computing (EC2) infrastructure.
In conclusion, with this research we contributed building and analysing TunUp, an open solution for evaluation, validation and tuning of data clustering algorithms, with a particularly focused on cloud services.
Our experiments show the quality and efficiency of tuning k-means on a set of public datasets.
The research also provides a Roadmap that gives indications of how the current system should be extended and utilized for future clustering applications, such as: Tuning of existing clustering algorithms, Supporting new algorithms design, Evaluation and comparison of different algorithms.
Arthouse Convergence Presentation: Branding, San Rafael July 2014Tim League
I gave this presentation at the West Coast Arthouse Convergence Regional Conference in San Rafael on July 10, 2014. The topic was "Building Your Brand." The program description was as follows:
"Building a cohesive brand for your theater that incorporates the unique qualities of your community can be daunting. How do you ensure consistency? What should be the message behind your brand? What does a “brand” even mean? Join us as we explore the national, regional and local branding that our cinemas deploy as we root ourselves in our communities."
Not sure why there are boxes around the logos in the SlideShare version. Ironic that in a show about brand, I violate brand standards with said boxes. They don't appear on the presentation version...
The amount of digital data in the new era has grown exponentially in recent years and with the development of new technologies, is growing more rapidly than ever before.
Nevertheless, simply knowing that all these data are out there is easily understandable, utilizing these data to turn a profit is not trivial.
The need of data mining techniques able to extract profitable insight information is the next frontier of innovation, competition and profit.
A data analytic services provider, in order to well-scale and exponentially grow its profit, has to deal with scalability, multi-tenancy and self-adaptability.
In big data applications, machine learning is a very powerful instrument but a bad choice regarding the algorithm and its configuration parameters can easily lead to poor results. The key problem is automating the tuning process without a priori knowledge of the data and without human intervention.
In this research project we implemented and analysed TunUp: A Distributed Cloud-based Genetic Evolutionary Tuning for Data Clustering.
The proposed solution automatically evaluates and tunes data clustering algorithms, so that big data services can self-adapt and scale in a cost-efficient manner.
For our experiments, we considered k-means as clustering algorithm, that is a simple but popular algorithm, widely used in many data mining applications.
Clustering outputs are evaluated using four internal techniques: AIC, Dunn, Davies-Bouldin and Silhouette and an external evaluation: AdjustedRand.
We then performed a correlation t-test in order to validate and benchmark our internal techniques against AdjustedRand.
Defined the best evaluation criteria, the main challenge of k-means is setting the right value of k, that represents the number of clusters, and the distance measure used to compute distances of each pair of points in the data space.
To address this problem we propose an implementation of the Genetic Evolutionary Algorithm that heuristically finds out an optimal configuration of our clustering algorithm.
In order to improve performances, we implemented a parallel version of genetic algorithm developing a REST API and deploying several instances in the Amazon Cloud Computing (EC2) infrastructure.
In conclusion, with this research we contributed building and analysing TunUp, an open solution for evaluation, validation and tuning of data clustering algorithms, with a particularly focused on cloud services.
Our experiments show the quality and efficiency of tuning k-means on a set of public datasets.
The research also provides a Roadmap that gives indications of how the current system should be extended and utilized for future clustering applications, such as: Tuning of existing clustering algorithms, Supporting new algorithms design, Evaluation and comparison of different algorithms.
5. How Does Your Music Magazine Attract/Address Your Audience?
1. 5. How Does Your Music Magazine
Attract/Address Your Audience?
2. ADDRESSING THE AUDIENCE
The mode of address used for my audience is colloquial and expletive
language which fits in well with the typical rocker on my front cover. It is
an informal way of writing but I believe it fits in better with the target
audience who are young adults. Colloquial language is particularistic as
only certain sub cultures will understand this. I have also used expletive
language as the stereotypical view of rock artists are that they swear a lot.
The word 'f**ing' is used on the front cover which is an example of this.To
attract my target audience, I have used colloquial and expletive language
as mentioned above as well the images I have used. My 'model' on the
front cover is a typical pop rock artist as she is white, has big hair,
heavy/bold makeup and black leather clothing. Seeing as this is the typical
image associated with this genre, it will attract my target audience.
Furthermore, if someone was to see this magazine on a shelf, they will
easily be able to tell which genre my music magazine is. From the image
on the front cover, to the expletive language and the name/masthead of
the magazine - Spark'd.
3. The white background shows The masthead varies throughout the
purity and it seeps through into magazine as it is shown in black at the
the strapline. This gives the idea front and white on some of the pages
to the audience that not inside. The black symbolises darkness
everything in the magazine is as well as the typical colour associate
going to be conflicting. The with rock. The red shows passion and
colours also symbolise a binary danger – for the music as well as the
opposition as it’s the idea of contents inside. This shows that there
good vs evil. You are also told are controversial views in the magazine
this as the word ‘independent’ as the black and red are both bold
show that the views inside are all colours. Also, this will attract my
very strong an opinionated. audience because they will see the
bold masthead standing out.
This list of artists will
also attract the
reader as they get a
The image of ‘Charlie’ shows a
taster of what is
feisty independent woman who
inside.
comes across as confident and
loud. This will attract the female
audience who believe in
independence as they will want
to follow Charlie. Furthermore,
The audience may relate to the the image is very large which will
strapline as a lot of young people attract fans of the rockstar –
nowadays have a very reckless therefore generating more sales.
attitude. This magazine is aimed
at people aged between 15 and
25 so the strapline may fit in
with the experiences of young
people. This is because a lot of
young adults drink, smoke and
do much about which creates The audience is also told that these worldwide bands
this reckless and carefree are going to be included inside the magazine which will
attitude. make their fans buy this magazine.
4. Having a variety of images which will
grab the readers’ attention because
they will see a wide range of people.
Eye catching writing which will
immediately draw the audiences’
attention
There’s a constant stylistic feature throughout The contents page will also grab the attention of the readers as
the magazine which shows in these two there’s a range of things inside. There’s a section for gigs, pages
pages. This creates consistency which gives on the latest music, tours and general information on stars and
out the message to the audience that there’s celebs. Therefore it’s not all about music because there are things
a consistency within the content of the about the everyday lifestyles of the singers as well.
magazine.