Text sentiment analysis and recommendation algorithm
Budget: $50 – $90 USD
Introduction: :
This project contains three parts of a big project. Text sentiment analysis and Recommendation system. I have described this project very deeply.
First part: systems have to take input from users about their current situation (current emotion ). And It have to identify the emotion of the user's current situation. And required keywords.
Example: I lost the job -> emotion: sadness keywords: job, lost
Second part systems have allowed users to upload their life moments with description (image or video with description). And the system has to identify the emotion of the description. And required keywords,
Example: It’s my birthday party -> emotion: happiness keywords: birthday, party
Thereafter, It has to store all the details. Also, users have an option to input a motivational quote, you can assign emotion of the motivational quote as emotion: motivation. And have to identify some keywords from that motivational quotes
Third part
This is the recommendation part. systems have to recommend a moment from their stored memories (second part). For the recommendation system will use three parameters
User personalities (https://www.16personalities.com/personality-types)
User current emotion and keywords (First part)
Available users memories (Second part)
User personalities
Don\t want to identify the personalities of the user. Because it’s my friend’s part. So, just use predefined personalities.you can refer from here (https://www.16personalities.com/personality-types)
Example for third part:
Parameter 1: User personality is Defender (It’s an assumption you may use only a personality for whole project)
Parameter 2: current emotion: sadness keywords: job
Parameter 3: Available users memories and motivational quotes
Results: Recommend a memory related user’s job related happy moments or motivational quotes
Note:
Emotions for the first part: happiness, love, anger, fear, sadness, less motivated, loneliness
Emotions for the Second part: happiness, motivation
In First part-. the user can input only one current situation at once.
In the second part A- users can upload a moment once at a time that can be a video or photo with description or motivational quote without description.
You can make any assumption based on this idea. (before ask me something)
Second part can run independently, which mean, user can upload their memories whatever time.
Technologies:
This project has two use two technologies
NLP text sentiment analysis
Recommendation
Development has to be done in Pandas. And for the text sentiment analysis I recommend SpaCy library, and for the recommendation I recommend the youtube recommendation algorithm.
Dataset : You can use any existing data set or may create one for the requirements..
Below is Only for the information
Our actual project is a Mental health advisor. In that project, first we analis the user personality and identify the user's current emotion and we will provide recommendations from their memories and external resources. Above part 1,2,3 are my parts others will do other parts.
This project contains three parts of a big project. Text sentiment analysis and Recommendation system. I have described this project very deeply.
First part: systems have to take input from users about their current situation (current emotion ). And It have to identify the emotion of the user's current situation. And required keywords.
Example: I lost the job -> emotion: sadness keywords: job, lost
Second part systems have allowed users to upload their life moments with description (image or video with description). And the system has to identify the emotion of the description. And required keywords,
Example: It’s my birthday party -> emotion: happiness keywords: birthday, party
Thereafter, It has to store all the details. Also, users have an option to input a motivational quote, you can assign emotion of the motivational quote as emotion: motivation. And have to identify some keywords from that motivational quotes
Third part
This is the recommendation part. systems have to recommend a moment from their stored memories (second part). For the recommendation system will use three parameters
User personalities (https://www.16personalities.com/personality-types)
User current emotion and keywords (First part)
Available users memories (Second part)
User personalities
Don\t want to identify the personalities of the user. Because it’s my friend’s part. So, just use predefined personalities.you can refer from here (https://www.16personalities.com/personality-types)
Example for third part:
Parameter 1: User personality is Defender (It’s an assumption you may use only a personality for whole project)
Parameter 2: current emotion: sadness keywords: job
Parameter 3: Available users memories and motivational quotes
Results: Recommend a memory related user’s job related happy moments or motivational quotes
Note:
Emotions for the first part: happiness, love, anger, fear, sadness, less motivated, loneliness
Emotions for the Second part: happiness, motivation
In First part-. the user can input only one current situation at once.
In the second part A- users can upload a moment once at a time that can be a video or photo with description or motivational quote without description.
You can make any assumption based on this idea. (before ask me something)
Second part can run independently, which mean, user can upload their memories whatever time.
Technologies:
This project has two use two technologies
NLP text sentiment analysis
Recommendation
Development has to be done in Pandas. And for the text sentiment analysis I recommend SpaCy library, and for the recommendation I recommend the youtube recommendation algorithm.
Dataset : You can use any existing data set or may create one for the requirements..
Below is Only for the information
Our actual project is a Mental health advisor. In that project, first we analis the user personality and identify the user's current emotion and we will provide recommendations from their memories and external resources. Above part 1,2,3 are my parts others will do other parts.