Loading...
Answers
MenuWhat are the best techniques for recognizing content topics and building recommendations?
Answers
1) Look through posts and just and tally which "side-topics" show up the most within the last week. Rank them. The top two side-topics for each group will be the most promising ones to suggest to that group in the future. You'll basically be making a 'word cloud', like this: https://www.jasondavies.com/wordcloud/
2) To test your new hypothesis, occasionally start making your own posts on the groups with links to articles about the most promising side-topics you've identified. Either make brand new posts, or cross-post from other groups. See how popular the posts are.
3) If not, move to the next most popular side-topic and do some tests with that.
4) Repeat steps 1 - 4 (each time you do step 1, use the most recent week of posts)
If you'd like more detailed advice on how to do this, and test its effectiveness with regard to your specific groups, let me know,
best,
Lee
1. To tackle the problem of extracting relevant topics of "key-words" from a text (posts, tags, conversation) a simple NER (Named Entity Recognition) system can be used. It can create a list of all the relevant Topics in the text.
2. Once you have the list, this list can be used in another DL algorithm - Recommendation System.
Challenges with a Recommendation System is that it requires a lot of pre-training data and a huge resource to train. (This is only viable in cases where you already have a good amount of tagged data and do not have any constraints in terms of using bigger resources).
3. Another simpler, faster but less accurate way is to use a clustering model ( can be from ML or DL depending on the data ). This approach creates multiple clusters and can tag each element in the NER list with one of the clusters.
Then using distance formula within the cluster one can find out the most relevant topics that are related to the element in the NER list.
If you'd like more details on the approach let me know.
Regards,
Deepesh
Related Questions
-
I am writing a book on artificial intelligence, anyone open to being interviewed about your experiences for the book?
I am happy to volunteer! I have a more "classical" background in mathematical statistics, and I have followed the distribution of artificial intelligence with great interest and curiosity; also because, I feel, that the actual application and real life-value of AI-implementations often drowns in technical aspects. So what is actually delivered is more the Data Scientists "wet dream" rather than something, that works in real life. If you are interested, feel free to contact me. Best regards Kenneth WolstrupKW
-
How can I aggregate data from online sources about a specific topic?
There are so many ways to do it... Do you need this data for yourself, or you are planning to make a product around it? From what I see you can use Twitter API and Facebook Graph API (Are you comfortable programming?) Most of the students are active on social media so you will find lots of data. Facebook graph API will give you a number of likes and comments to all the posts of you competitors. You can analyze all the posts of your competitors. Using Twitter API you can get all the twits that use certain hashtags or mentions. If you are not into coding, but still want to get social media information, you can take a look at tools like IBM Watson ANalytics ($30 for personal use), it natively connects to Twitter API, and you don't have to be a programmer at all. It is intuitive and easy to learn. Analytics Canvas connects to Facebook Graph API (it's free for 30 days of trial). Unfortunately, you would not be able to collect any personal information from social media at large scale (age, income, gender, etc.), because it violates all the laws about privacy on the Internet. You can use census data instead. Google Sheets are a very handy tool if you are planning to use this information for personal research. You can set up a spreadsheet and add some Java script to make it collect all information from competitor's blogs, and also sites like Reddit. Finally, you can try web scraping (it's not the best, but can speed up the process). A tool like OutWitHub will collect information from websites (such as website reviews) based on the structure you provide (select html tags). You can collect thousands of reviews in one day if you automate it (paid version). Very easy to use. Note: not all the websites are open to this method, review their policies to make sure you are not violating their terms of service. Reviews belong to the website where they were published. If you REALLY need personal data (like how much they earn and how much they spend, etc.), just print out 100 questionnaires and go to Student Union Building of Dalhousie University. Most of the students will share any personal data in exchange for a Tim Horton's gift card that gets them a free coffee. It is probably the least technical and fastest way to get all the data you need. Hope this helps.OT
-
Affordable analytics platform for product, marketing, sales, UX, tech support and employee satisfaction?
You mention, that you can code and maintain yourself, and at the same time it sounds like your data can be dispersed across multiple sources. And you want to minimise license cost. In my business we use R a lot for both analysis and reporting. It is free (open source), but you will have to build programs. But it will read any format, and also create output to any destination you want. So you could start off with a mix of R, Excel and pdf, just to get things going. However, it could make sense for you to build a database already so you familiarise yourself with data warehouse thinking, since you want to expand with marketing automation. At that point you will need a database for monitoring response, sales etc. So it is important to build the right foundation as ealy as possible. If you don't want to code, but want point-and-click, there is boatloads of software for that, but probably more license cost (unless you can find open source for that). So If I were you, I would start off with something smaller. After all, you want to focus on the value you create for the business and your colleagues, and the time you save, rather than a smooth IT-infrastructure for this. I have lots of experience building reporting and analysis in the areas you mention, so if you want to discuss further, feel free to set up a call. Good look with your development. Best regards Kenneth WolstrupKW
-
Which recommendation system is best for content website which we easily can integrate with asp.net project?
"content" and asp.net aren't specific enough to answer this question as is.CW
-
I am writing a book on artificial intelligence, what are the biggest challenges that you have had applying AI to your business or to clients?
I have written short blogs on how can AI be beneficial to lead your business smartly with less human efforts and more automated, here you can check it - https://www.linkedin.com/pulse/how-develop-ai-app-like-siri-shail-sanghvi/ 2) https://www.linkedin.com/pulse/how-develop-chatbot-importance-shail-sanghvi/SS
the startups.com platform
Copyright © 2025 Startups.com. All rights reserved.