# First Team Meeting Worksheet


## Team Members Present

* Cam Raker
* Liam Prevelige
* Noah Jerris
* Joshua Pasaribu
* Alex Kruger

## I. Identify a Common Vision
*You’ve all voted on a common idea and themes. Now is the time to work through your commonalities and find a unifying vision between all of you. Answer the following for each of you. This is the time to speak your mind. Be honest with each other.*

Some system that encourages people to discover good books and read. Not sure exactly what direction this will go, but some discussion about Goodreads (social elements & what it lacks) and improving coventional recommendation systems using ML.

We expect the recommendation algorithm will be the most important and most difficult piece of our project. We would also like to make a tool with limited barriers to signup & recommendations.

### Commonalities
*Who makes up your team? What are some common things you are interested in? Tell each other about the things you put down on the survey and expand on some of your passions.*

* All chose BookFinder because of interest in implementation & algorithm
* None of us really read that often; ranging from ~2 books/year to ~15 books/year
* All expressed interest in reading more often
* Most experience with web-development (vs mobile)
* Share some experience with: Python, C, JavaScript/React, SQL, NoSQL, Java, TensorFlow
* Prefer not to work with low-level design

### Inspiration
*What are some things each of you is inspired by?*

* Algorithms that seem like they know you
* Intuitive, low-barrier to use designs
* User-centered design that's accessible to wide base of users (i.e. not expensive, intuitive UI)
* Creating something that people find useful for extended periods of time
* Learning new, interesting technology
* Building something rather than fully dependent on outside, pre-built tools

### Problems of Interest
*What problems are you looking to address? Why?*

* It's hard to find new books
* Often a tradeoff between reading variety and reading preference
* People don't read as much as they would like
* Difficult to know whether you like a book without spending significant time reading it
* People lose reading momentum
* Everyone reads a lot when they're young and read less as they age (at least among our group)
* Reading is often less engaging than playing videogames
* Books are expensive, especially physical ones

### Identify
*Which of the above is most interesting to all of you?*

Combination of problems:
* We were all interested in how to maintain momentum, as it's a problem that has affected us all
* Within the larger problem, very interested in (a) how to find books and (b) forms of gamification within reading

## II. Narrow In
*Now let's try narrowing in on a problem that interests all of you. Make sure to go around the table and listen to everybody on your team without interruption.*

* We find the recommendation algorithm to be the most interesting part
* We also think that a Strava-type social media aspect could be a very useful piece for the user
* The combination of these ideas would also improve reading momentum (finding better books, encouraging reading via friend-based competition)

#### Coolness
*What could be cool about this potential project?*

* Thinking about how we can tag books for the recommendation algorithm - many categories for correlation, determining which are effective
* Finding parallels between recommendation models & social media from other industries and applying them to reading
* Many components for splitting work and opportunities to build on existing platform ideas

#### Challenges
*What could be challenging / unfun about this potential project?*

* Creating the common infrastructure for social media component (depending on how creative we can get with it) might feel like busywork/copy & paste
* Creating or finding test data for the recommendation model

#### Success
*What does success look like for this project?*

* Creating a functional algorithm in the fall, then expanding on this algorithm with social media-esque intfrastructure
* At a high level, improving people's reading discovery experience and continual progress