Theory
1.
What is Theory? Theory is the underlying logical explanation of for
example one or more hypothesis. It’s the “why” in an answer to a
question, its an explanation to an observed pattern. Theory is for
explaining “why” something is.
But
what is not Theory? As we read in the text “What theory is not” we find
that it’s quite a lot actually. The 5 main points are data, references,
list of variables, diagrams and hypotheses. Data is not theory as it’s
merely observations of occurrences and not explanations as to why these
things are occurring. References is not theory either as they themselves
do not contain the so important explanation to an occurrence as well,
its just points to where someone else might have had a theory but
without the possibility to absorb the explanation first hand in for
example a paper. Hypotheses are mere assumptions or predictions and can
not be theory without logical arguments as to why this hypotheses came
true. etc
However these 5 might be parts to help creating a theory, but them by their selves are not theory.
2. I choose the paper “A Computational model of “Active Vision” for Visual Search in Human-Computer interaction” (http://www.tandfonline.com/doi/full/10.1080/07370024.2011.625237)
from the journal HUMAN-COMPUTER INTERACTION that has an impact factor of 1.476
The
goal of the paper is to make way for a model that is suited for
active-vision interfaces. The paper has been made around 4 central
questions regarding just that. When do the eyes move? Where do the eyes
move? What can be perceived in a fixation? and what information is
integrated between eye movements? The paper answers all these questions
using already know models to find the best one to predict eye movement. I
think its fairly hard to categorise this as I’ve never done it before,
but if i have to i think it might be a nr 1 in the table provided by the
text from Gregor, and that would be Analysis as this paper uses
existing models and analyses them i search for the beast match for a
“future” active-vision model. It does however answer some questions
using these models, and that one might say is some kind of prediction or
explanation. But as it mainly focuses on testing other models i
categorised it as Analysis.
3.
The benefits are that using the Analysis model is that its maybe easier
to understand as a reader since it’s step by step based with
description and analysis of the subject. And by doing just that you can
combine more models or theories as in my text where they analyse quite a
few different models to find the most suitable for the task.
The
limitations of this theory model is that it doesn’t really explain or
predict anything. It just takes it for what it is and repacks it and
thus not generating that much new information. Another limitation
connected to the paper might be that since they focused around these 4
questions it was also “only” what they did. There might have been a lot
more to the subject that they could have learned, but by focusing so
narrowly they might have missed things.
fredag 2 november 2012
torsdag 1 november 2012
Thoughts on Theme 1
Week 44
This first week was divided into two different topics whereas one of them was more in line with our education where we looked at research papers and journals to find out what is “good” and “high quality” information. We learned about Impact factors that is a measurement to evaluate how “good” or how “important” a journal is. And we had to find a journal which had an impact factor with a value over 1, as this was considered a “good” journal. And from these journals we had to choose a paper that we thought was interesting. These papers however do not have impact factors, but only the journal. So to say that a certain paper is of good quality or not is a little bit harder when we don't have a grading system for it. Another thing about journals is that they have to be around for a while to have good values, since it takes at least a year for an impact factor to be calculated, and if a journal has been around longer it’s also more probable that its been cited more and thus gained a higher impact factor. For me this was the first time on KTH that we got to read some research papers that were connected to our field of study, and this was very nice and i do think that I will have use for this in the future when I’m going to write my master thesis. The instructions as how to find these papers could have been a lot better tho as I spend quite some time just getting a feel for the system.
The second part was more philosophical based and talked about what is knowledge and can we ever truly know something? And for this we read a “short” book from Bertrand Russel that was called “The Problems of Philosophy (1912)”. A book that even thou quite old, had information about the way we perceive things that I found is still relevant for today’s society. I thought that even though it was a lot to take in, in such short time, and that we should probably have read it several times to get a deeper understanding, It was very interesting. I’m still not quite sure as where this fits into our education, but it makes us maybe pause a little and ask ourselves more questions.
This first week was divided into two different topics whereas one of them was more in line with our education where we looked at research papers and journals to find out what is “good” and “high quality” information. We learned about Impact factors that is a measurement to evaluate how “good” or how “important” a journal is. And we had to find a journal which had an impact factor with a value over 1, as this was considered a “good” journal. And from these journals we had to choose a paper that we thought was interesting. These papers however do not have impact factors, but only the journal. So to say that a certain paper is of good quality or not is a little bit harder when we don't have a grading system for it. Another thing about journals is that they have to be around for a while to have good values, since it takes at least a year for an impact factor to be calculated, and if a journal has been around longer it’s also more probable that its been cited more and thus gained a higher impact factor. For me this was the first time on KTH that we got to read some research papers that were connected to our field of study, and this was very nice and i do think that I will have use for this in the future when I’m going to write my master thesis. The instructions as how to find these papers could have been a lot better tho as I spend quite some time just getting a feel for the system.
The second part was more philosophical based and talked about what is knowledge and can we ever truly know something? And for this we read a “short” book from Bertrand Russel that was called “The Problems of Philosophy (1912)”. A book that even thou quite old, had information about the way we perceive things that I found is still relevant for today’s society. I thought that even though it was a lot to take in, in such short time, and that we should probably have read it several times to get a deeper understanding, It was very interesting. I’m still not quite sure as where this fits into our education, but it makes us maybe pause a little and ask ourselves more questions.
söndag 28 oktober 2012
Research publications/Theory of science
Journal:
Data & Knowledge Engineering
(http://www.journals.elsevier.com/data-and-knowledge-engineering/)
Impact Factor:1.422
The aim of the journal is to identify, investigate and analyze the underlying principles in the design and effective use of Data & Knowledge Engineering systems.
Research paper:
This Paper was taken from the Journal mentioned above.
(http://www.sciencedirect.com/science/article/pii/S0169023X12000237)
The paper is called “From humor recognition to irony detection: The figurative language of social media” and is about automated humor and irony processing in short texts or one-liners on the Internet. By applying this model the authors wanted to try and find key processes that makes us recognising and understanding humor and irony. They tried this by using different scenarios where humor and irony appears in different situations and looked at their relevance to build the model. Over 50000 short texts “tweets” were analyzed for this paper. I do not know how and where these “tweets” were collected from, but an observation might be that maybe these tweets all were in English and therefore this is not a general interpretation for humor and irony as it might be subjective to cultural differences..
1. Sense data is a term that Russell created to describe how we actually perceive things, with our senses. For example how we interpret light, colors, sound, when we touch things, smells and so on. The reason for coming up with this was that he thought that there wasn't a way to really describe what a specific individual is experiencing when having a “sensation”. As there is no rule to what is a “right” sensation or not.
2. A Statement of fact is something you have experienced, something you are acquainted with and thereby know is true, I could say that a statement of fact is that my current jacket is blue, and everyone that has seen it will know that this is indeed true. Where as a proposition is when we know something but we are not acquainted with this thing personally, so its more know by description. For example we know that mount Everest is the highest mountain in the world, even thou many of us haven't been there.
3. Russell describes definite descriptions with example of the phrases “a so-and-so and “the so-and-so”. Where a so-and-so is something general or ambiguous, like a car or a buss. where as “the so-and-so” describes something unique. Like a person with its attribute that is unique to this particular person. For example “The King of Sweden”. This describes one specific person and could not be any other and thereby a definite description.
4. Russel argues about if we really can know what true knowledge is, All the things we know for sure, we might only think we know. We can never be 100% sure of that what we know is true. If one person thinks something its probably just an opinion, but if more people have the same opinion about this knowledge then it is more likely that it’s true. He also talks about the differences between philosophical and scientific knowledge where he thinks that there really aren't that big differences.
Data & Knowledge Engineering
(http://www.journals.elsevier.com/data-and-knowledge-engineering/)
Impact Factor:1.422
The aim of the journal is to identify, investigate and analyze the underlying principles in the design and effective use of Data & Knowledge Engineering systems.
Research paper:
This Paper was taken from the Journal mentioned above.
(http://www.sciencedirect.com/science/article/pii/S0169023X12000237)
The paper is called “From humor recognition to irony detection: The figurative language of social media” and is about automated humor and irony processing in short texts or one-liners on the Internet. By applying this model the authors wanted to try and find key processes that makes us recognising and understanding humor and irony. They tried this by using different scenarios where humor and irony appears in different situations and looked at their relevance to build the model. Over 50000 short texts “tweets” were analyzed for this paper. I do not know how and where these “tweets” were collected from, but an observation might be that maybe these tweets all were in English and therefore this is not a general interpretation for humor and irony as it might be subjective to cultural differences..
The Problems of Philosophy (1912) by Russel
Questions
1. Sense data is a term that Russell created to describe how we actually perceive things, with our senses. For example how we interpret light, colors, sound, when we touch things, smells and so on. The reason for coming up with this was that he thought that there wasn't a way to really describe what a specific individual is experiencing when having a “sensation”. As there is no rule to what is a “right” sensation or not.
2. A Statement of fact is something you have experienced, something you are acquainted with and thereby know is true, I could say that a statement of fact is that my current jacket is blue, and everyone that has seen it will know that this is indeed true. Where as a proposition is when we know something but we are not acquainted with this thing personally, so its more know by description. For example we know that mount Everest is the highest mountain in the world, even thou many of us haven't been there.
3. Russell describes definite descriptions with example of the phrases “a so-and-so and “the so-and-so”. Where a so-and-so is something general or ambiguous, like a car or a buss. where as “the so-and-so” describes something unique. Like a person with its attribute that is unique to this particular person. For example “The King of Sweden”. This describes one specific person and could not be any other and thereby a definite description.
4. Russel argues about if we really can know what true knowledge is, All the things we know for sure, we might only think we know. We can never be 100% sure of that what we know is true. If one person thinks something its probably just an opinion, but if more people have the same opinion about this knowledge then it is more likely that it’s true. He also talks about the differences between philosophical and scientific knowledge where he thinks that there really aren't that big differences.
onsdag 24 oktober 2012
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