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china 's generous 1mdb bid seen reaping it big returns in malaysia
china keeps an eye on visiting tiger freed by russian president
0
hezbollah targets qaeda gathering along border with syria
belarus tightens security along the border with ukraine
0
obama calls for international front against is
obama vows to save iraqis stranded on mountain
0
who abandoned 3 boeing planes at the airport ?
police abandon posts in lesotho , fear for lives
0
ebola uk : nhs staff ' panicked ' after suspected ebola cases
uk says investigating 2 suspected mers cases
0
philippines , canada pledge to further boost relations
philippines saves 100 after ferry sinks
0
n. korea agrees to talks with south
johor crowns its fifth sultan
0
two palestinians die in attacks on israelis ahead of kerry visit
palestinian official slams israel 's stone-throwing bill
0
obama struggles to soothe saudi fears as iran talks resume
myanmar struggles to finalize voter lists for sunday polls
0
south korea declares end to mers outbreak
north korea delegation meets with south korean officials
0
volkswagen skids into red in wake of pollution scandal
volkswagen 's " gesture of goodwill " to diesel owners
2
two australians killed in kenya after bus crashed into river
permalink to two killed in germany train accident
0
dozens of egyptians hostages taken by libyan terrorists as revenge for airstrikes
egyptian boat crash death toll rises as more bodies found in nile
0
president heading to bahrain
president xi : china to continue help to fight ebola
0
obama is right : africa deserves better leadership
obama waiting for midterm to name attorney general
0
putin spokesman : doping charges appear unfounded
the latest on severe weather : 1 dead in texas after tornado
0
to explain further vector space models , basically a document is characterized by a vector .
a document is represented as a vector .
5
if a term appears in the document then its value in the vector is non-zero .
a document is represented as a vector and each dimension corresponds to a separate term .
2
the algebraic model for representing text documents and objects as vectors of identifiers is called the vector space model .
a possible use for a vector space model is for retrieval and filtering of information .
1
p ( a ) , or the probability that the student is a girl regardless of any other information .
it is mainly used to calculate the probability of one event ’ s outcome given that a previous event happened .
1
for instance , a events schedule at an exhibition is sometimes called a program .
for instance , a finalized schedule of events at an exhibition is sometimes called a program .
4
define value of optimal solution recursively .
characterise structure of an optimal solution .
4
it was first used in the smart information retrieval system .
it is used in information retrieval and was first used in the smart information retrieval system .
4
a term which occurs in the document has a value in the vector of non-zero .
the order in which the terms appear in the document is lost in the vector space representation .
1
if a term exists in a document , its value in the vector is not equal to zero .
a document is represented as a vector , with each dimension corresponding to a separate term .
2
a page that is linked to by many pages with high pagerank receives a high rank itself .
a link to a page is seen as a vote of support .
1
p ( b ) ( a.k.a. the normalizing constant ) is the prior or marginal probability of b .
p ( b ) is the prior or marginal probability of b , and acts as a normalizing constant .
5
in the vector space model a document is represented as a vector .
a possible use for a vector space model is for retrieval and filtering of information .
1
one of its uses is calculating posterior probabilities given observations .
it is usually used to calculate posterior probabilities given observations .
5
finally , the order in which the terms appear in the document is lost in the vector space representation .
a term which occurs in the document has a value in the vector of non-zero .
1
several different ways of computing these values , also known as ( term ) weights , have been developed .
many different ways of calculating these values , also known as ( term ) weights , have been developed .
4
to derive the theorem , we begin with the definition of conditional probability .
in probability theory , the prior and conditional probabilities of two random events are related by bayes ' theorem .
2
it doesn 't take into account any information about b , so it is " prior " .
however an object cannot be cast to a class which is no relative of it .
0
thus , the program is the best plan for action that is produced .
thus , the " program " is the optimal plan of action that is being produced .
5
this means that inheritance is used when types have common factors and these would be put into the superclass .
they do not have to be written in a computer language .
0
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
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 .
5
the methodology takes much less time rather than naive methods .
this is a much quicker method than other more naive methods .
5
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
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
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
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
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 .
5
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 .
5
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
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
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 β€œ … is a kind of ” relationship .
0
the definition of term depends on the application .
the definition of a term depends on the application .
5
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
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
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
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
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
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
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
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
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
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
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
in the vector space model a document is represented as a vector .
the vector space model are the documents which are represented as β€œ bags of words ” .
1
when any sub-problem is met again , it can be found and re-used to solve another problem .
it was intended to allow existing code to be used again with minimal or no alteration .
2
p ( a ) , or the probability that the student is a girl regardless of any other information .
later versions of pagerank ( see the below formulas ) would assume a probability distribution between 0 and 1 .
0
when a document is represented as a vector , each dimension corresponds to a separate term .
the value of a vector is non-zero if a term occurs in the document .
1
the vector space model are the documents which are represented as β€œ bags of words ” .
the limitations of the vector space model are thus .
2
the vector space model is one of these methods , and it is an algebraic model .
in vector space model , the documents from which the information is to be retrieved are represented as vectors .
1
the vector is then constucted of the frequency of eacher word ( dimension ) .
the basic idea is to represent each document as a vector of certain weighted word frequencies .
3
it does not take into account any information about b and therefore is considered β€œ prior ” .
it doesn 't take into account any information about b , so it is " prior " .
5
the vector space model has several disadvantages .
a document has representation as a vector .
1
every dimension is precisely related to a separate term .
a document is represented as a vector , with each dimension corresponding to a separate term .
4
this means that inheritance is used when types have common factors and these would be put into the superclass .
occasionally it is advantageous to differentiate between these uses , as it is not necessarily noticeable from context .
0
the idea of inheritance is to reuse the existing code with little or no modification at all .
the idea of inheritance in oop refers to the formation of new classes with the already existing classes .
3
a document is represented as a vector and each dimension corresponds to a separate term .
when a document is represented as a vector , each dimension corresponds to a separate term .
5
since it is a formal theorem , bayes ' theorem holds in all popular interpretations of probability .
as a formal theorem , bayes ' theorem is valid in all common interpretations of probability .
5
the methodology takes much less time rather than naive methods .
the method is more effiecent than naive methods .
5
this means that inheritance is used when types have common factors and these would be put into the superclass .
this can be useful when the number of times a word appears is not considered important .
0
the value of a vector is non-zero if a term occurs in the document .
if the term doesn ’ t occur within the document , the value in the vector is zero .
3
the value of a vector is non-zero if a term occurs in the document .
the order in which the terms appear in the document is lost in the vector space representation .
1
the similarity measures largely identify the retrieval efficiency of a particular information retrieval system .
it is used in information retrieval and was first used in the smart information retrieval system .
1
the vector space model is one of these methods , and it is an algebraic model .
the vector space model has the following limitations : 1 .
1
the theorem is often used when we have observations and wish to compute posterior probabilities .
it is usually be used to compute posterior probabilities given observations .
4