TL; DR

We will create an expert search engine by utilizing the dark data that sleeps in the company and the data related to meetings. Such a guy

This will allow you to find an in-house expert and a contact path to that expert.

1. Background. .. ..

1.1 What is work style reform?

Jitahara is often said to have work style reforms.

Jitahara: Forcing employees to leave the company, such as "Don't work overtime" or "Return on time", without specific measures to reduce overtime hours.

There is. Serious people will return as they were told ~~ You will have to take it home and work overtime. ** That's stupid! !! !! ** **

1.2 Meetings ... Would you like to reduce it?

According to Asahi Shimbun

Loss of wasteful meetings at large companies: 670,000 hours a year and 1.5 billion yen

That's right. I will listen to it straightforwardly.

** Can you reduce meetings? ** ** ** If we can reduce by 1.5 billion yen, shouldn't we be rewarded as much as Mr. Ghosn? ** **

The world is full of so much know-how! !! !! !!

But why doesn't it change over the years? .. .. .. .. Personally, after all, I don't think I'm serious about reducing the number of meetings and time. In short, the know-how that comes out from google is just a blunder.

1.3 Meeting ... Will you use the data?

Even if it is a venture, if the scale exceeds 300 people *, the things that each employee can do will be limited.

According to the definition of SMEs, it depends on the type of business, but [it seems to be a large company if it exceeds at least 300 people](https://ja.wikipedia.org/wiki/%E4%B8%AD%E5%B0% 8F% E4% BC% 81% E6% A5% AD)

That doesn't mean you're not doing anything. Instead of reducing the number of meetings without thinking (abuse) as is done in your company or my company, let's take advantage of it ** even a little.

2. Issues and solution policies

2.1 Challenges that are likely to be a large company

As an issue that tends to occur in an organization where the number of employees including the group exceeds a certain number,

I want to know about 〇〇, but ** I don't know who to ask **
I understand the listener, but I don't know him ** so it's hard to talk to him suddenly **

What's the matter? There is, right?

So, let's set this as an issue to be solved.

2.2 Solution policy

Isn't it accumulated in vain and is the first in Dark Data? I will try to utilize the conference data that seems to be.

Dark data Refers to "data that may create value within a company but is not utilized"

It is not used because it is only accumulated. Even if I googled, there were no examples of its use. What a waste.

If it comes out normally, my google skill is very disappointing. .. .. ..

2.3 Characteristics of meeting data

Now let's consider the characteristics of conference data.

merit

(Generally) open data internally
Covers all employees (although management may be private)
real time

Demerit

** May be personal information **
If so, it may be necessary to consider the handling policy (troublesome)

There are some disadvantages, but ... let's try it first!

3. Data collection and preprocessing

For more information, please see here [https://boomin.yokohama/archives/1619)

4. Machine learning

It's been long, so see here.

5. Network analysis

It's been long, so see here.

6. Visualization

Vue + Vuex + [Vuetify](https://vuetifyjs.com/ja Developed using /).

6.1 First, the Home screen!

If the home screen is dull, some people may just go home. So, I did my best to ** feel cool on my own basis ** (misallocation)

6.2 Search for experts

Select Keyword Search from the left pane menu to search for people by word.

To! If you search for the word machine learning, you will find ** the Minister of Education, Culture, Sports, Science and Technology **. By the way, AI looks like this.

In addition, the color is a color for each cluster by clustering people who have similar remarks to some extent. It might have been better to set it by political party here, but it's ** annoying ** so I'll leave it as it is.

6.3 Search for connections

Next is the connection search. From Member's Search, search for Prime Minister Abe's connections (people with similar remarks here).

I see. .. .. .. (When I looked at this in the parliamentary minutes data, I didn't get any impressions.) I'm sure it would be a little interesting if we could feed the actual meeting data in-house. .. .. ..

6.4 Search for connections

It's finally time to search for connections (what I wanted to do the most). Then Prime Minister Abe and his sword? Let's examine the connection with Finance Minister Taro Aso.

Based on the content of the remarks, Mr. Toshio Beppu is sandwiched on the way. This area depends on the trained model, so I'll leave it for the time being.

Next, let's examine the connection between Prime Minister Abe and Representative Taro Yamamoto. (Because he was a member of parliament who came up with something)

On the way, three people are caught. Is that so?

6.5 Suggestion of search target word

Since there are many words that can be searched and many people are targeted, validation is performed before issuing a search query. However, it is difficult to know what kind of word is OK, so when you start typing a word, we have implemented a function to display search word candidates.

Now you can search for any word, but you can rest assured!

7 Development impression

What I thought about making so far is that ** UX design and UI design are important **. .. .. ..

Preparation of learning data, cleansing, morphological analysis, machine learning, and API development were all not that difficult. I think it's because the goal was clear as it was.

However, I started to make the front end without having a clear image, so I repeated that it was neither uh nor uh. Thanks to that, it's hard to feel that the source code isn't cool either. .. .. ..

I don't think this screen is good for me, but I'm not sure what to do with it.

8 Finally, for work style reform

Here, I showed the screen based on the minutes of the Diet, but I decided to use the learning data for the meeting data of my company (without permission). I think that you will receive various opinions, so please take them positively.

That? Who knows this? Oh, I'm lucky to know the connection if I search with this YO!

Everyone thinks

Does this person do this kind of work? Then, let's talk a little and try to brainstorm the idea of the project!

I would be happy if you think about it.

[PYTHON] I tried HR Tech to develop an expert search engine by machine learning in-house meeting information