Challenge 

 The mobile games sector seems to be one of the fast growing industries due to the rising of   mobile market . With the advancement of mobile technology , mobile devices can now be used   as a mobile media centre . One of the emerging areas is also in using it for gaming . Because of   Google Play store , today numerous different games are offered to every Smartphone user . This   diversity in supply is a good thing , but it also disables users to find games they would like to   play . I wanted to make a personalized mobile game recommendation system which takes into   consideration various factors those are responsible for game selection and installation . 

 There were two main goals of this experiment : 

 ⦁   To study the effect of various factors those are responsible for game selection and   installation . 

 ⦁   To propose a better recommendation system that incorporates all the factors in making   recommendation and compares the performance of our proposed approach with that   of the classical one . 

 Selection 

 We decided to use mind mapping and brainstroming in order to collect all the major factors   responsible for game selection and categorize them according to group which they found   similarity with . Mind mapping steps includdes picking out the good stuff from the invidiuals   notes and his new ideas . cluster the good ideas and identify the insights related to each cluster   and look for connections between clusters . 

 Application 

 Factors responsible for game selection are found out from : 

 ⦁   Research papers using keywords ( mobile games/ computer games ) . 

 ⦁   Game players ( All the top game players and game developers ) . 

 7 Research papers were read to find out all the important factors that lead to game selection   and installation . 

 24 undergraduate were invited and participated in this research . 

 Major points in Game design found out through research papers . 

 Computer Games : Exploration , and educational . ( Amory , A. , Naicker , K. , Vincent . , & Adams , C.   ( 1999 ) ) , Challenge , Fantasy , curiosity . ( Malone , T. W. ( 1980 ) ) , Positive Reinforcement , increase   social . ( Squire , K. ( 2002 ) ) , 4.Self - Determination , competence , psychological satisfaction , Game 

 variable , Intuitive controls , Presence , Motivation , Enjoyment , Preference for future play ,   Change in well - being , Vitality , Self - esteem , Mood / effect . ( Ryan , R.M. , Rigby , C.S. & Przybylski    ( 2006 ) ) , Fun , play , rules , goals , interactive , adaptive , outcomes , feedback , ego gratification ,   competition , problem - solving , interaction , and emotion . ( Prensky , M. ( 2001 ) ) 

 Mobile Games : Game should be challenging , personal liking and vision , social contents ,   communication -social playability , Motivational , inspirational 

 Internet Games : Reasons People Play Online Games , Passing Time , Entertainment , Challenge   Competition , Fantasy and Roll Playing , Self - Presentation , Social Interaction , Triggered   Emotions , Energetic , Engagement , Joy , Happiness , Love , Enthusiasm , Anxiety , Fear , Hate ,   Worry , Distress , Anger , Hostility , Disgust 

 Major Factors responsible find out through brain storming session : Action , puzzle , games ,   multiplayer , Game - ram , graphics , Mood , free time , recreation , Unique idea , Requirements and   compatibility , Simple controls , Education , Social like pub - g , Easy and interesting stages ,   Storyline , Reviews , Description , new idea , Same interest like sports , More stages and big game ,   More manual then automatic , Movie based . ( good story ) . 

 Major Factors responsible for android games selection find out through personal interaction :   Download size , social interaction , Gameplay and prize , Graphics , Friend circle and lists , Maps   and gameplay , Offline availability , Insta - ads and recommendation from friends etc , Better   understanding the game/ judge through icons , Mood effect.(recreation / bore ) , Interest of   games . 

 Factors responsible for video games selection find out through personal interaction :   Competition.(multiplayer(fps)),Storyline ( single player games ) , YouTube/ insta ads / reviews ,   Trailer / game play , Brand of games , Skill / interaction / tools , Mood effect , Graphics / content / game   play , Prizes , Values / aesthetics , Maps / rules / fun , Fare games matches . 

 Our preliminary analysis is based on the factors that are found out using by the 5 subjects who   were approached to find out all the factors responsible . Then , a brain storming session was   done with the 5 subjects to find all the factors other than the factors found out in research   papers . 

 Insight 

 By applying mind mapping , we divided all the factors into three major groups : Game specific ,   Device specific , Socio - psychological factors . 

 Game specific : All the factors that Depends on the Game we are taking into consideration were   added into Game specific Group . 

 Device specific : All the factors that Depends on the specification of device we are using to play   the Game were added into Device specific Group . 

 Socio - psychological factors : All the factors that are related to social and psychological state of 

 the user playing the game were added into Socio - psychological factors group . 

 Approach 

 Further to find pattern in this huge amount of data we used similarity scores . after taking rating   from game users , Some users considered as subject for recommendation , Compared rating of   users with other users and computed similarity scores , Used similarity scores to make prediction   for each game which is not played , Recommended game with highest prediction value . 

 Organization 

 IIT Roorkee 

 Additional Feedback 

 This research will also help game developers and game companies to make better games for the 

 game players according to their need . 


EMAIL: 
ID_NUM: 
NAME_STUDENT: 
PHONE_NUM: 
STREET_ADDRESS: 
URL_PERSONAL: 
USERNAME: 

### Task: You are a PII (Personal Identity Information) Detection. Given a essays written by students, you have to identify ONLY the following:
NAME_STUDENT - The full or partial name of a student that is not necessarily the author of the essay. This excludes instructors, authors, and other person names.
EMAIL - A student’s email address.
USERNAME - A student's username on any platform.
ID_NUM - A number or sequence of characters that could be used to identify a student, such as a student ID or a social security number.
PHONE_NUM - A phone number associated with a student.
URL_PERSONAL - A URL that might be used to identify a student.
STREET_ADDRESS - A full or partial street address that is associated with the student, such as their home address.
### Input: Challenge 

 The mobile games sector seems to be one of the fast growing industries due to the rising of   mobile market . With the advancement of mobile technology , mobile devices can now be used   as a mobile media centre . One of the emerging areas is also in using it for gaming . Because of   Google Play store , today numerous different games are offered to every Smartphone user . This   diversity in supply is a good thing , but it also disables users to find games they would like to   play . I wanted to make a personalized mobile game recommendation system which takes into   consideration various factors those are responsible for game selection and installation . 

 There were two main goals of this experiment : 

 ⦁   To study the effect of various factors those are responsible for game selection and   installation . 

 ⦁   To propose a better recommendation system that incorporates all the factors in making   recommendation and compares the performance of our proposed approach with that   of the classical one . 

 Selection 

 We decided to use mind mapping and brainstroming in order to collect all the major factors   responsible for game selection and categorize them according to group which they found   similarity with . Mind mapping steps includdes picking out the good stuff from the invidiuals   notes and his new ideas . cluster the good ideas and identify the insights related to each cluster   and look for connections between clusters . 

 Application 

 Factors responsible for game selection are found out from : 

 ⦁   Research papers using keywords ( mobile games/ computer games ) . 

 ⦁   Game players ( All the top game players and game developers ) . 

 7 Research papers were read to find out all the important factors that lead to game selection   and installation . 

 24 undergraduate were invited and participated in this research . 

 Major points in Game design found out through research papers . 

 Computer Games : Exploration , and educational . ( Amory , A. , Naicker , K. , Vincent . , & Adams , C.   ( 1999 ) ) , Challenge , Fantasy , curiosity . ( Malone , T. W. ( 1980 ) ) , Positive Reinforcement , increase   social . ( Squire , K. ( 2002 ) ) , 4.Self - Determination , competence , psychological satisfaction , Game 

 variable , Intuitive controls , Presence , Motivation , Enjoyment , Preference for future play ,   Change in well - being , Vitality , Self - esteem , Mood / effect . ( Ryan , R.M. , Rigby , C.S. & Przybylski    ( 2006 ) ) , Fun , play , rules , goals , interactive , adaptive , outcomes , feedback , ego gratification ,   competition , problem - solving , interaction , and emotion . ( Prensky , M. ( 2001 ) ) 

 Mobile Games : Game should be challenging , personal liking and vision , social contents ,   communication -social playability , Motivational , inspirational 

 Internet Games : Reasons People Play Online Games , Passing Time , Entertainment , Challenge   Competition , Fantasy and Roll Playing , Self - Presentation , Social Interaction , Triggered   Emotions , Energetic , Engagement , Joy , Happiness , Love , Enthusiasm , Anxiety , Fear , Hate ,   Worry , Distress , Anger , Hostility , Disgust 

 Major Factors responsible find out through brain storming session : Action , puzzle , games ,   multiplayer , Game - ram , graphics , Mood , free time , recreation , Unique idea , Requirements and   compatibility , Simple controls , Education , Social like pub - g , Easy and interesting stages ,   Storyline , Reviews , Description , new idea , Same interest like sports , More stages and big game ,   More manual then automatic , Movie based . ( good story ) . 

 Major Factors responsible for android games selection find out through personal interaction :   Download size , social interaction , Gameplay and prize , Graphics , Friend circle and lists , Maps   and gameplay , Offline availability , Insta - ads and recommendation from friends etc , Better   understanding the game/ judge through icons , Mood effect.(recreation / bore ) , Interest of   games . 

 Factors responsible for video games selection find out through personal interaction :   Competition.(multiplayer(fps)),Storyline ( single player games ) , YouTube/ insta ads / reviews ,   Trailer / game play , Brand of games , Skill / interaction / tools , Mood effect , Graphics / content / game   play , Prizes , Values / aesthetics , Maps / rules / fun , Fare games matches . 

 Our preliminary analysis is based on the factors that are found out using by the 5 subjects who   were approached to find out all the factors responsible . Then , a brain storming session was   done with the 5 subjects to find all the factors other than the factors found out in research   papers . 

 Insight 

 By applying mind mapping , we divided all the factors into three major groups : Game specific ,   Device specific , Socio - psychological factors . 

 Game specific : All the factors that Depends on the Game we are taking into consideration were   added into Game specific Group . 

 Device specific : All the factors that Depends on the specification of device we are using to play   the Game were added into Device specific Group . 

 Socio - psychological factors : All the factors that are related to social and psychological state of 

 the user playing the game were added into Socio - psychological factors group . 

 Approach 

 Further to find pattern in this huge amount of data we used similarity scores . after taking rating   from game users , Some users considered as subject for recommendation , Compared rating of   users with other users and computed similarity scores , Used similarity scores to make prediction   for each game which is not played , Recommended game with highest prediction value . 

 Organization 

 IIT Roorkee 

 Additional Feedback 

 This research will also help game developers and game companies to make better games for the 

 game players according to their need .
### Output: 