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these subproblems are not , however , independent .
it is similar to divide and conquer , however is differentiated as its subproblems are not independent .
4
the key to dynamic programming is to find the structure of optimal solutions .
in general , dynamic programming is used on optimisation problems , where the most efficient solution is needed .
4
when a document is represented as a vector , each dimension corresponds to a separate term .
each dimensions corresponds to a separate terms .
3
bayes theorem is a mathematical formula used to calculate conditional probabilities .
bayes ' theorem relates the conditional and marginal probabilities of two random events .
4
lucky joe likes to predict the colour of the ball he selects and he is 80 % accurate .
joe records all of his results and about 0.5 % of the time he accidently records the wrong results .
1
thus , the program is the best plan for action that is produced .
the other method is the top down approach which is a method that combines memorization and recursion .
0
it is usually used to calculate posterior probabilities given observations .
it is usually be used to compute posterior probabilities given observations .
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the methodology takes much less time rather than naive methods .
the method takes much less time than naive methods .
5
the methodology takes much less time rather than naive methods .
this is a much quicker method than other more naive methods .
5
the definition of term is dependent on the application .
the definition of term depends on the application .
5
this means that inheritance is used when types have common factors and these would be put into the superclass .
it is similar to divide and conquer , however is differentiated as its subproblems are not independent .
0
characterise structure of an optimal solution .
use these optimal solutions to construct an optimal solution for the original problem .
2
the theorem is often used when we have observations and wish to compute posterior probabilities .
it is usually used to calculate posterior probabilities given observations .
3
occasionally it is advantageous to differentiate between these uses , as it is not necessarily noticeable from context .
it also provides a way to generalize du to the " is a " relationship between classes .
0
construct an optimal solution from computed values .
define value of optimal solution recursively .
4
occasionally it is advantageous to differentiate between these uses , as it is not necessarily noticeable from context .
it is similar to divide and conquer , however is differentiated as its subproblems are not independent .
0
when a document is represented as a vector , each dimension corresponds to a separate term .
the basic idea is to represent each document as a vector of certain weighted word frequencies .
2
when a document is represented as a vector , each dimension corresponds to a separate term .
each dimension corresponds to a separate term .
3
mathematicians use the word to describe a set of rules which anyone can follow to solve a problem .
however an object cannot be cast to a class which is no relative of it .
0
whilst bayesians describe probabilities in terms of beliefs and degrees of uncertainty .
at the same time , bayesians describe probabilities in terms of beliefs and degrees of uncertainty .
5
it is used in information filtering , information retrieval , indexing and relevancy rankings .
it is used in information filtering , indexing , relevancy rankings and information retrieval .
5
in probability theory , bayes ' theorem relates the conditional and marginal probabilities of two random events .
bayes ' theorem is useful in evaluating the result of drug tests .
1
outbound , links from your page to others .
dangling , links to a page which has no links to others .
1
vector space representation results in the loss of the order which the terms are in the document .
in vector space model , the documents from which the information is to be retrieved are represented as vectors .
1
in computer science ; dynamic programming is a way of solving problems consist of overlapping subproblems and optimal substructure .
however , the key in dynamic programming is to determine the structure of optimal solutions .
3
if a term appears in the document , the terms value in the vector is non-zero .
vector space representation results in the loss of the order which the terms are in the document .
1
in vector space model , the documents from which the information is to be retrieved are represented as vectors .
finally , the order in which the terms appear in the document is lost in the vector space representation .
1
for instance , a finalized schedule of events at an exhibition is sometimes called a program .
the typical example could be of a finalized schedule of events at an exhibition .
3
several different ways of computing these values , also known as ( term ) weights , have been developed .
several different ways of computing these values , additionally known as ( term ) weights , have been developed .
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if a term exists in a document , its value in the vector is not equal to zero .
if a term appears in the document then its value in the vector is non-zero .
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a hyperlink to a page counts as a vote of support .
a link to a page is seen as a vote of support .
5
this means that inheritance is used when types have common factors and these would be put into the superclass .
the main problem is divided into sub problems which are solved and stored for future use .
0
most of these languages provide an “ extend ” keyword , which is used to subclass another .
for example , a program could exist to model different forms of transport .
0
for instance , a finalized schedule of events at an exhibition is sometimes called a program .
for example , a schedule of events at an exhibition is sometimes called a programme .
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the value of a vector is non-zero if a term occurs in the document .
each document is a vector where each word is a dimension .
1
the theorem is often used when we have observations and wish to compute posterior probabilities .
it is often used to calculate posterior probabilities given observations .
4
other possible uses for vector space models are indexing and also to rank the relevancy of differing documents .
in this classic model the term specific weights in the document vectors are products of local and global parameters .
1
the correct answer can be computed using bayes ' theorem .
bayes ' theorem is useful in evaluating the result of drug tests .
1
• p ( b | a ) is the conditional probability of b given a .
p ( a | b ) is the conditional probability of a , given b .
3
since the pagerank is the most important algorithms which is used in the google engine .
the pagerank is a recursive algorithm used by google to determine which webpages are more important than others .
3
nevertheless , the patent is assigned to the university of stanford and not to google .
however , the patent is assigned to stanford university and not to google .
5
this means that inheritance is used when types have common factors and these would be put into the superclass .
it is therefore used to create relationships between one object and another .
0
in the vector space model a document is represented as a vector .
a document is represented as a vector , and each dimension corresponds to a separate term .
3
p ( b ) is the prior or marginal probability of b , and acts to normalise the probability .
p ( b ) ( a.k.a. the normalizing constant ) is the prior or marginal probability of b .
4
this can be useful when the number of times a word appears is not considered important .
the easiest way to look at inheritance is as an “ … is a kind of ” relationship .
0
in probability theory , bayes ' theorem relates the conditional and marginal probabilities of two random events .
bayes ' theorem relates the conditional and marginal probabilities of two random events .
4
the definition of term depends on the application .
the definition of a term depends on the application .
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break up the problem different smaller subproblems .
a problem with overlapping subproblems means that the same subproblems may be used to solve many different larger problems .
2
inheritance is a method of forming new classes using predefined classes .
inheritance in object oriented programming is a way to form new classes using classes that have already been defined .
5
so the same rule applies with keywords and indeed longer phrases .
single words , keywords and occasionally longer phrases are used for terms .
3
there is also conditional probability which is usually interested in the way variables relate to each other .
the pagerank is a recursive algorithm used by google to determine which webpages are more important than others .
0
thus , the program is the best plan for action that is produced .
thus , the " program " is the optimal plan for action that is produced .
5
inheritance is a basic concept in object oriented programming .
inheritance in object oriented programming is a way to form new classes using classes that have already been defined .
3
programming , in this sense , means finding an acceptable plan of action .
programming , in this sense , means finding an acceptable plan , an algorithm .
4
the vector space model has some limitations : 1 .
the vector space model has several disadvantages .
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using the vector space model for information retrieval models all pages and queries as high-dimensional sparse vectors .
a possible use for a vector space model is for retrieval and filtering of information .
4
one of the most famous schemes is tf-idf weighting .
one of the best known schemes is tf-idf ( term frequency-inverse document frequency ) weighting .
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a document is represented as a vector , with each dimension corresponding to a separate term .
a document has representation as a vector .
3
vector space representation results in the loss of the order which the terms are in the document .
the order in which terms appear in the document is lost in a vector space representation .
4
p ( a ) is the probability of the student being a girl ( which is 2 / 5 ) .
what is the probability this student is a girl ?
2
the basic idea is to represent each document as a vector of certain weighted word frequencies .
if a term appears in the document , the terms value in the vector is non-zero .
1
therefore , the " program " is the optimal plan for action that is produced .
the " program " is the optimal plan for action that is produced .
5
this is highly used in dynamic programming .
there are four steps in dynamic programming : 1 .
2
other ways of computing these values , or weights , have been developed .
many different methods of calculating these values , sometimes known as ( term ) weights , have been developed .
4
it is usually be used to compute posterior probabilities given observations .
it is used to compute posterior probabilities given observations .
4
in probability theory , bayes ' theorem relates the conditional and marginal probabilities of two random events .
bayes theorem is a mathematical formula used to calculate conditional probabilities .
3
p ( b ) is the prior or marginal probability of b , and acts as a normalizing constant .
p ( b | a ) is the conditional probability of b given a .
1
a website ’ s page rank , is how ‘ important ’ it is on the web .
a variation of the pagerank method bases the importance of a webpage on how many visits the page gets .
3
in computer science ; dynamic programming is a way of solving problems consist of overlapping subproblems and optimal substructure .
dynamic programming is a very powerful mathematical technique , often utilised in programming , for solving optimization problems .
4
the most popular is tf-idf weighting .
one of the most famous schemes is tf-idf weighting .
4
this method is used in the google toolbar , which reports back actual site visits to google .
in order to prevent spamming , google releases little information on the way in which a pagerank is calculated .
1
to achieve this , the programmer has to note generalisations and similarities about various aspects of the program .
mathematicians use the word to describe a set of rules which anyone can follow to solve a problem .
0
construct an optimal solution from computed values .
the last point would be to construct an optimal solution from the computed values .
4
if the term doesn ’ t occur within the document , the value in the vector is zero .
if a term appears in the document , the terms value in the vector is non-zero .
3
this is a much quicker method than other more naive methods .
the method takes much less time than naive methods .
4
p ( b ) is the prior or marginal probability of b , and acts to normalise the probability .
p ( a ) , or the probability that the student is a girl regardless of any other information .
1
inheritance in object oriented programming is a way to form new classes using classes that have already been defined .
inheritance in object oriented programming is where a new class is formed using classes which have allready been defined .
4
they also inherit the attributes and methods of its superclass .
the new classes are called derived classes and they inherit the behaviours and attributes of the base classes .
3
a term which occurs in the document has a value in the vector of non-zero .
a document is represented as a vector , with each dimension corresponding to a separate term .
2
if a term appears in the document , the terms value in the vector is non-zero .
a term which occurs in the document has a value in the vector of non-zero .
5
the order in which terms appear in the document is lost in a vector space representation .
in vector space model , the documents from which the information is to be retrieved are represented as vectors .
1
the vector space model has some limitations : 1 .
limitation : there is some limitation of vector space model .
5
however , the vector space model has limitations .
the limitations of the vector space model are thus .
4
the method can be abused when people deliberately link to sites in order to raise a site 's pagerank .
mathematicians use the word to describe a set of rules which anyone can follow to solve a problem .
0
when a document is represented as a vector , each dimension corresponds to a separate term .
to explain further vector space models , basically a document is characterized by a vector .
2
the basic idea is to represent each document as a vector of certain weighted word frequencies .
a term which occurs in the document has a value in the vector of non-zero .
1
programming , in this sense , means finding an acceptable plan of action .
programming means finding a plan of action .
4
google ’ s payoff is that it gets to track the behaviour of actual users .
after this , it is using this to pick the best overall path .
0
this means that inheritance is used when types have common factors and these would be put into the superclass .
there is also conditional probability which is usually interested in the way variables relate to each other .
0
bayes ’ theorem was names after rev thomas bayes and is a method used in probability theory .
as a formal theorem bayes theorem is valid in all common interpretations of probability .
3
dynamic programming solves problems by combining the solutions of subproblems .
the key to dynamic programming is to find the structure of optimal solutions .
4
terms are basically the words or any indexing unit used to identify the contents of a text .
in this classic model the term specific weights in the document vectors are products of local and global parameters .
2
the vector space model are the documents which are represented as “ bags of words ” .
in vector space model , the documents from which the information is to be retrieved are represented as vectors .
2
thus , the " program " is the optimal plan of action that is being produced .
the easiest way to look at inheritance is as an “ … is a kind of ” relationship .
0
to achieve this , the programmer has to note generalisations and similarities about various aspects of the program .
the advantage being the less time consumption in comparison to other amateur methods .
0
subclasses are said to extend or specialise their superclasses .
subclasses are said to ‘ extend ’ superclasses .
4
it is also called the posterior probability because it is derived from or depends upon the specified value of b .
it is also called the subsequent probability because it is derived from or depends upon the specified value of b .
3
this can be useful when the number of times a word appears is not considered important .
it is mainly used to calculate the probability of one event ’ s outcome given that a previous event happened .
0
java allows object inheritance .
inheritance is one of the basic concepts of object oriented programming .
1
mathematicians use the word to describe a set of rules which anyone can follow to solve a problem .
instead , a new object is made to inherit properties of objects which already exist .
0