Web Analytics Understanding user behavior and ... - pace university

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Only 3 cases spent more time on the site with out clicking further. So these three cases are not classified by this rule. As a result these rule sets give an insight into how people behave on the web site. This information can be used to address the problems associated with web and making it more interactive. The analysis of users tells what their choice has been after coming to the site. As a result we can use this information for making a more user friendly site so that the web experience is improved and goals are achieved. G: Analytics Derived Most people know in less than three seconds (
No of users: 103 2.Pace university No of users: 90 2 http://csis.pace.edu/~benjamin 1. Combination of Paul Benjamin No of users: 2 2. Paul Benjamin No of users: 10 3 http://csis.pace.edu/~bergin 1. Combinations of Bergin No of users: 81 2. Combinations of Karel No of users: 17 3. Combinations of patterns No of users: 14 4. http://csis.pace.edu/pclc 1.Combinations of pace No of users: 45 2. pace university No of users: 32 3. Combinations of computer learning center No of Users: 19 Note: Ignore the case for the keywords 2.sexual health curriculum 1. Paul Benjamin office hours 1. abbey 2. key image 1. Cheltenham computer training 2. Microsoft logo gear Majority of the users after coming to the site have again searched for the specific information by clicking two or three links. The returned pages may contain the keyword as part of information in the page or as another hyper link. As a result the user again searches on the returned page for the information based on his/ her interests. Hence, the returned page which is just a static page with keyword info is again leading the user to look further for the final destination. 10 156 122 63
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Web Analytics Understanding user be
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CONTENTS Acknowledgement………
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web site what he or she needs. But
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a decision tree to help a financial
Page 9 and 10:
With data mining, a retailer could
Page 11 and 12: Occam's Razor (Specialized to Decis
Page 13 and 14: Pete Brown Tall Heavy No None John
Page 15 and 16: Attribute: Height Reference: positi
Page 17 and 18: D) Now let’s examine to see if th
Page 19 and 20: Similarly, we now choose another te
Page 21 and 22: See5/C5.0 See5/C5.0 is a sophistica
Page 23 and 24: Attribute Case 1 Case 2 Case 3 ....
Page 25 and 26: The file hypothyroid.names looks li
Page 27 and 28: Explicitly-defined attributes The n
Page 29 and 30: Attributes defined by formulas The
Page 31 and 32: the value of flight time is the num
Page 33 and 34: The main window of See5 has six but
Page 35 and 36: Many of the options have default va
Page 37 and 38: :...TT4 61: :...referral source in
Page 39 and 40: else if on thyroxine equals f then
Page 41 and 42: The Problem Server log files from C
Page 43 and 44: A: Server log files The following a
Page 45 and 46: 24.4.255.251 - - [02/Jul/2001:16:59
Page 47 and 48: 128.48.26.71 / "http://www.google.c
Page 49 and 50: w%5D=&wf%5B1%5D%5Br%5D=%2B&wf%5B1%5
Page 51 and 52: 200.205.16.130 - - [05/Jul/2001:19:
Page 53 and 54: 200.205.16.130 - - [05/Jul/2001:19:
Page 55 and 56: E: Creation of data sets for See5/C
Page 57 and 58: pace university,1,0,0,no. pace univ
Page 59 and 60: PACE,1,0,0,no. pace university,1,1,
Page 61: Time: 0.0 secs Explanation: -------
Page 65 and 66: A Real Life Scenario Kat walks into
Page 67 and 68: DHTM can be used to create links ba
Page 69 and 70: A) Website: http://csis.pace.edu/~b
Page 71 and 72: As the page loads links based on th
Page 73 and 74: http Referrer: Null When the http r
Page 75 and 76: Case 1: When the user came to the w
Page 77 and 78: As the page loads links based on th
Page 79 and 80: Hence, the administrator tool gives
Page 81 and 82: Issues and Scope: Cleaning the 412M
Page 83: an understanding will lead to some
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