Goals

• Continue assessing the requirements and difficulty of the most popular potential projects
• Select a project in which everyone is interested

Discussion

The AI Search project that was initially very popular, grew less favorable, as did the Reading Leveler. Multiple members pointed out ways in which these projects were overly complex or difficult to define. In particular, on the Reading Leveler, pre-existing conventions for defining reading levels are rather poorly defined. Alex stated that he consulted a friend studying education, and discovered that reading levels are only fairly well defined through about the fifth grade. Chris pointed out that it would be very difficult to assess the effectiveness and accuracy of any such application without rigid rules. Ryan pointed out that the AI Search project could end up being much more complicated than the other alternatives.

The board game recommendation engine seemed the best option to everyone. The team would have access to experts, and the project clearly met all the specifications given by the instructor.

Results

The team agreed that the board game recommendation engine would be the group’s capstone project.

Attendance

• Ryan McGowan
• Chris Powers (scribe)
• Alex Burkhart
• David Albert

Location

Dreese Labs

Goals

Assess the requirements and difficulty of the most popular potential projects.

Discussion

As previously determined, the AI Search and Board Ultimatum projects were the most popular among groupmembers. David was especially interested in the AI Search project. Alex was less interested in the AI Search project. Chris pointed out that working with existing code may be less desirable than choosing our own methods. Alex liked the board game recommendation project because it would be useful and interesting, and as a member of a board game group, he believes that the system would be actually used. Chris suggested that the board game project would better resemble previous projects provided by the instructor, and, as such, would be safer, while still interesting. Alex pointed out that he knows many serious board game players through the club, so the team would have easy access to experts in the area.

The “Reading Leveler” (a reading level classification engine), proposed by Ryan, was also popular among group members. The team would have access to some experts, potentially professors and elementary school teachers. David and Ryan suggested that the engine would likely involve some type of semantic processing engine, and Chris points out that this may make the project unnecessarily complex for the scope of the capstone project.

Results

Everyone gained a better understanding of the general requirements of each of these popular proposals, but none were definitively selected.

Attendance

• Ryan McGowan
• Chris Powers (scribe)
• Alex Burkhart
• David Albert

Location

Dreese Labs

Goals

• Continue discussing topic ideas.
• Choose a team name.

Discussion

We came up with several more topics. Those created during our first meeting (1-6) are included for completeness.

1. AI Search
2. Board Ultimatum – Alex
3. Determine the time of day for a given photo – David
4. Music Genre Classifier – David
5. Poetry Generator – Chris
6. Music Generator from arbitrary data – Ryan
7. Craig’s list recommendations – Ryan
8. Blog categorizer – Ryan
9. Twitter friend suggester – Ryan
10. Log analysis – Ryan
11. Schedule Helper – Ryan
12. Beauty Pageant – Ryan
13. Reading Leveler - Determine what reading level a given piece of text is. – Ryan
14. Text-to-Origin Machine - Guess the origin of a block of text using only the text itself. – Ryan

Creating a Team Name

Finding the concept of overly zealous agile and scrum teams rather hilarious the name Scrum Ninjas was suggested. However, we were worried that it might be a name that an overly zealous agile and/or scrum team might actual use. Not wanting to be confused with people who actually think a name like Scrum Ninjas is clever we decided alterations were necessary.

Accordingly, we made the name more ridiculous by appending Jedi Masters and finally prepending Dinosaur Riding.

Results

During this meeting we decided that topic 1 did not sounds as interesting or fun as 2 or 13. Thus, we adjourned with the intention of picking one or the other during our next meeting.

We picked the team name: Dinosaur Riding Scrum Ninja Jedi Masters (DRSNJM).

Attendance

• Ryan McGowan (scribe)
• Chris Powers
• Alex Burkhart
• David Albert

Location

Dreese Labs

Goals

Make introductions and start brainstorming topic ideas.

Discussion

We came up with several topics:

1. AI Search
2. Board Ultimatum – Alex
3. Determine the time of day for a given photo – David
4. Music Genre Classifier – David
5. Poetry Generator – Chris
6. Music Generator from arbitrary data – Ryan

Results

By the end of this meeting we were deciding between topics 1 and 2.

Attendance

• Ryan McGowan (scribe)
• Chris Powers
• Alex Burkhart
• David Albert

Location

Dreese Labs

Goals

Get components connected for fourth timebox.

Discussion

Ryan has nearly finished building the “expert interface” for extracting expert game recommendations. Chris has already connected the filtering and scoring engines. Alex and Chris are working on filtering on the number of players. David is working on connecting the neural network to the mongo database after dropping plans to connect to a non-mongo database.

Results

Ryan finished the expert interface, complete with results in a mongo collection. The last part for him to work on is randomizing games pulled from the database. David was able to run his neural network code and generate a database of garbage values. Chris and Alex completed connecting the components of the attribute search and were running successful queries from the interface.

Attendance

• Ryan McGowan
• Chris Powers (scribe)
• Alex Burkhart
• David Albert

Location

Ryan McGowan’s house