Systems and methods for generating personalized item descriptions

1. A method for dynamically generating a product description personalized for a target user account, the method comprising:

obtaining, from one or more servers via a communication network, at least one of product description data associated with a product or product comment data associated with the product;

generating, based on at least one of the product description data or the product comment data, a product description template comprising fields to be populated;

storing the product description template in a memory;

identifying, by a recommender system, a first set of user accounts, each user account of the first set of user accounts having a similarity score with a target user that is above a similarity threshold;

obtaining, from one or more servers via the communication network, a first set of comment data associated with a product of interest, the first set of comment data originating from the first set of user accounts;

generating comment-based description data, based on comment data from the first set of comment data, wherein generating comment-based description data comprises:

analyzing comment data of the first set of comment data, wherein the comment data of the first set of comments are associated with the product of interest and comprise information items, and wherein the analyzing comprises identifying an information item in the comment data, and associating a tag to the information item, and wherein analyzing product data or comment data is performed using at least one of part-of-speech tagging, dependency parsing, or domain knowledge, and

wherein the first set of user accounts is identified by the recommender system using at least one of collaborative filtering, content-based filtering, and a knowledge-based system;

storing the comment-based description data in the memory; and

generating, for aural or visual presentation, a product description for the target user account, wherein generating the product description comprises:

retrieving the product description template from the memory;

retrieving the comment-based description data from the memory; and

populating the fields of the retrieved product description template based on the retrieved comment-based description data.

2. The method of claim 1 , further comprising:

detecting, from the target user account, an access request to the product of interest,

wherein the generating the product description is performed in response to the detecting, from the target user account, the access request to the product of interest.

3. The method of claim 1 , wherein generating the product description template comprises:

analyzing the product description data and the product comment data, wherein the analyzing comprises:

identifying an information item in the product data (production description data and product comment data);

associating a tag to the information item;

identifying a structure of the product data; and

creating a product description template comprising the structure and at least one field, each field being linked to a tag.

4. The method of claim 1 , further comprising generating and storing in the memory a plurality of product description templates.

5. The method of claim 1 , wherein

the product description data relates to the product of interest or to similar products, and

the product comment data relates to the product of interest or to similar products.

6. The method of claim 1 , wherein the product description data originate from a product provider and the product comment data originate from a set of certified user accounts.

7. The method of claim 6 , wherein the populating the fields of the retrieved product description template comprises selecting comment-based description data based on an input date of comment data or with an engagement value of the user account with respect to the product of interest.

8. The method of claim 1 , wherein populating comprises:

selecting a field in the product description template, the field being linked to a tag; and

selecting an information item of the comment-based description data that is associated with the tag.

9. The method of claim 1 , wherein

analyzing comprises creating a list including a plurality of information associated with a same tag, and

populating comprises selecting, for a field in the production description template linked to the tag, an information item from the list.

10. The method of claim 1 , wherein analyzing comprises:

selecting a second set of comment data amongst the first set of comment data, the selection being based on a priority score wherein the priority score includes at least one of a number of likes of the comment data, a number of dislikes of the comment data, a number of shares of the comment data, or a number of replies to the comment data.

11. The method of claim 1 , wherein

generating a product description template further comprises attributing an importance score to the product description template;

storing in the memory comprises storing the importance score; and

generating the product description comprises:

retrieving from the memory a plurality of product description templates and their respective importance scores, the importance scores being different; and

concatenating the plurality of product description templates based on their importance scores.

12. The method of claim 11 , wherein the product description templates are concatenated according to a decreasing importance score.

13. The method of claim 12 , wherein at least two product description templates have the same importance and the generating the product description comprises:

retrieving from the memory the two product description templates;

receiving a target-user input;

selecting one of them based on the target-user input.

14. The method of claim 13 , wherein the target-user input comprises an input made by the target user account for a product different from the product of interest.

15. The method of claim 1 , further comprising:

receiving an identifier of a product of interest via a recommender system that uses a second set of user accounts;

obtaining the second set of user accounts; and

selecting the first set of user accounts amongst the second set of user accounts.

16. The method of claim 15 , wherein the first set of user accounts is selected amongst the second set of user accounts, based on at least one of: a similarity score between the target user account and a similar user account, the number of inputs made by a similar user account, or an engagement value of the target user account with respect to the product of interest.

17. A system for dynamically generating a product description personalized for a target user account, the system comprising:

a memory storing instructions; and

control circuitry communicably coupled to the memory and configured to access the memory and execute the instructions to:

obtain, from one or more servers via a communication network, at least one of product description data associated with a product or product comment data associated with the product;

generate, based on at least one of the product description data or the product comment data, a product description template comprising fields to be populated;

store the product description template in the memory;

identify, by a recommender system, a first set of user accounts, each user account of the first set of user accounts having a similarity score with a target user that is above a similarity threshold;

obtain, from one or more servers via the communication network, a first set of comment data associated with a product of interest, the first set of comment data originating from the first set of user accounts;

generate comment-based description data, based on comment data from the first set of comment data, wherein the control circuitry configured to generate comment-based description data is further configured to:

analyze comment data of the first set of comment data, wherein the comment data of the first set of comments are associated with the product of interest and comprise information items, and wherein the analyzing comprises identifying an information item in the comment data, and associating a tag to the information item, and wherein analyzing product data or comment data is performed using at least one of part-of-speech tagging, dependency parsing, or domain knowledge, and

wherein the control circuitry configured to identify the first set of user accounts using the recommender system is configured to use at least one of collaborative filtering, content-based filtering, and a knowledge-based system;

store the comment-based description data in the memory; and

generate, for aural or visual presentation, a product description for the target user account, wherein generating the product description comprises:

retrieving the product description template from the memory;

retrieving the comment-based description data from the memory; and

populating the fields of the retrieved product description template based on the retrieved comment-based description data.