Learning Launch and Virtual Agent for University Campus – Experiment 

 Among the Design thinking approach ,   “ Learning Launch :   is a quick and   inexpensive Experiment with Market . It is about testing the key customer   segment and checking our assumption and a hypothesis . The idea is to learn by   testing . At the beginning of the experiment , we decide what must be true for this   to be a Good Idea , and at the end of the experiment we should determine   whether our key assumptions are true or not true . 

 In our experiment , we thought of testing a Virtual Agent - a computer application/   Robot would provide counselling to the Students for the first day of Joining . This   application will work on Natural Language Processing and will have answer for   around 50 FAQ ’s commonly expected from the students who joins the university   on the first day . We selected Learning Launch as a tool to experiment this project ,   as it is cost effective and it directly tests customer perception and provides the   results quickly . 

 If more than 7 students ( from the day ’s average of 150 joiners ) speak to this   virtual agent for their doubts clarifications , i.e 5 % of the total population and   without again going to Human counselor , it is considered as success and this   Project can be taken up in a big way and can be implemented for other campuses   as well . If every person , who talk to this Virtual Agent , again approaching the   human counsellor , it considered to be not suitable . Either more sophisticated   language processing is required , or more data base need to be added , or people   mind set need to be changed to use more and more virtual agents . 

 On the day of Opening , learning launch was tested , we have selected 3   volunteers , just to explain to the students about what services are offered   through this virtual agent . They have covered almost 100 % population and   provided them with the opportunity to talk to the Virtual Agent .   There were 12   students approached this virtual agents and 5 of them could not get their answers   due to their spoken accent , the same question was answered by the virtual agent   when a volunteer repeated it . So by and large , the mission was success , but one   of our initial assumption was true , that is this is an useful tool , but more technical   upgradation ( more semantic , context based understanding is required for the   robot / virtual machine ) but people are excited to talk to a virtual agent and   patient enough to experiment . 

 So the key assumption of improvement required in the language got proved with   the data and it has been taken for further development for large scale and more   fine tuned application development . 


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: Learning Launch and Virtual Agent for University Campus – Experiment 

 Among the Design thinking approach ,   “ Learning Launch :   is a quick and   inexpensive Experiment with Market . It is about testing the key customer   segment and checking our assumption and a hypothesis . The idea is to learn by   testing . At the beginning of the experiment , we decide what must be true for this   to be a Good Idea , and at the end of the experiment we should determine   whether our key assumptions are true or not true . 

 In our experiment , we thought of testing a Virtual Agent - a computer application/   Robot would provide counselling to the Students for the first day of Joining . This   application will work on Natural Language Processing and will have answer for   around 50 FAQ ’s commonly expected from the students who joins the university   on the first day . We selected Learning Launch as a tool to experiment this project ,   as it is cost effective and it directly tests customer perception and provides the   results quickly . 

 If more than 7 students ( from the day ’s average of 150 joiners ) speak to this   virtual agent for their doubts clarifications , i.e 5 % of the total population and   without again going to Human counselor , it is considered as success and this   Project can be taken up in a big way and can be implemented for other campuses   as well . If every person , who talk to this Virtual Agent , again approaching the   human counsellor , it considered to be not suitable . Either more sophisticated   language processing is required , or more data base need to be added , or people   mind set need to be changed to use more and more virtual agents . 

 On the day of Opening , learning launch was tested , we have selected 3   volunteers , just to explain to the students about what services are offered   through this virtual agent . They have covered almost 100 % population and   provided them with the opportunity to talk to the Virtual Agent .   There were 12   students approached this virtual agents and 5 of them could not get their answers   due to their spoken accent , the same question was answered by the virtual agent   when a volunteer repeated it . So by and large , the mission was success , but one   of our initial assumption was true , that is this is an useful tool , but more technical   upgradation ( more semantic , context based understanding is required for the   robot / virtual machine ) but people are excited to talk to a virtual agent and   patient enough to experiment . 

 So the key assumption of improvement required in the language got proved with   the data and it has been taken for further development for large scale and more   fine tuned application development .
### Output: 