METHOD AND SYSTEM FOR INTERACTIVE SEARCHING BASED ON SEMANTIC SIMILARITY OF SEMANTIC REPRESENTATIONS OF TEXT OBJECTS
There is provided a method and a system for generating a graphical representation. A search request comprising an indication of a text object is received and a semantic representation of the search request is generated. One or more documents each satisfying a similarity condition with respect to the semantic representation of the search request are obtained, followed by the identification of one or more of: a respective set of paragraphs that each satisfies the similarity condition; a respective set of sentences that each satisfies the similarity condition; and a respective set of words that each satisfies the similarity condition. Then a graphical representation of at least a portion of each one of: the respective set of paragraphs, the respective set of sentences, and the respective set of words is generated.
1 . A method for generating a graphical representation in response to a search request, the method being executed by at least one processor, the method comprising:
receiving, from a client device, the search request comprising an indication of a text object;
generating a semantic representation of the search request;
obtaining, by using a trained model, one or more documents, each one of the one or more documents satisfying a similarity condition with respect to the semantic representation of the search request;
identifying, within each one of the one or more documents, one or more of:
a respective set of paragraphs that each satisfies the similarity condition with respect to the semantic representation of the search request;
a respective set of sentences that each satisfies the similarity condition with respect to the semantic representation of the search request; and
a respective set of words that each satisfies the similarity condition with respect to the semantic representation of the search request; and
generating, for display at the client device and for each one of the one or more documents, a graphical representation of at least a portion of each one of: the respective set of paragraphs, the respective set of sentences, and the respective set of words.
2 . The method of claim 1 , wherein the at least one processor is connected to the client device and has access to the trained model.
3 . The method of claim 1 , wherein the trained model is a machine learning (ML) model having been trained to generate and compare semantic representations of text objects.
4 . The method of claim 1 , wherein the text object comprises one of: a word, a sentence, a paragraph, and a document.
5 . The method of claim 1 , wherein the generating the semantic representation of the search request is based on the indication of the text object.
6 . The method of claim 1 , wherein the similarity condition with respect to the semantic representation of the search request is satisfied when each one of a plurality of semantic similarity scores obtained from a comparison of the semantic representation of the search request with each one of one or more document representations is indicative of a semantic similarity between the search request and a respective document of the one of more documents.
7 . The method of claim 6 , wherein each one of the plurality of semantic similarity scores is indicative of the semantic similarity between the search request and the respective document of the one of more documents when each one of the respective semantic similarity scores is above a threshold.
8 . The method of claim 7 , further comprising:
determining the threshold based on a number of the one or more documents and the respective semantic similarity scores.
9 . The method of claim 1 , wherein:
each one of the respective set of paragraphs satisfies the similarity condition with respect to the semantic representation of the search request when each one of a plurality of semantic similarity scores obtained from a comparison of the semantic representation of the search request with each one of the respective set of paragraphs is indicative of a paragraph semantic similarity between the search request and the respective set of paragraphs;
each one of the respective set of sentences satisfies the similarity condition with respect to the semantic representation of the search request when each one of a plurality of semantic similarity scores obtained from a comparison of the semantic representation of the search request with each one of the respective set of sentences is indicative of a sentence semantic similarity between the search request and the respective set of sentences; and
each one of the respective set of words satisfies the similarity condition with respect to the semantic representation of the search request when each one of a plurality of semantic similarity scores obtained from a comparison of the semantic representation of the search request with each one of the respective set of words is indicative of a word semantic similarity between the search request and the respective set of words.
10 . The method of claim 1 , wherein the graphical representation comprises a respective detailed view for each one of the one or more documents, the detailed view comprising the respective set of similar paragraphs, the respective set of similar sentences, and the respective set of similar words.
11 . A system for generating a graphical representation in response to a search request, the system comprising:
a non-transitory storage medium storing computer-readable instructions thereon; and
at least one processor operatively connected to the non-transitory storage medium, the at least one processor, upon executing the computer-readable instructions, being configured for:
receiving, from a client device, the search request comprising an indication of a text object;
generating a semantic representation of the search request;
obtaining, by using a trained model, one or more documents, each one of the one or more documents satisfying a similarity condition with respect to the semantic representation of the search request;
identifying, within each one of the one or more documents, one or more of:
a respective set of paragraphs that each satisfies the similarity condition with respect to the semantic representation of the search request;
a respective set of sentences that each satisfies the similarity condition with respect to the semantic representation of the search request; and
a respective set of words that each satisfies the similarity condition with respect to the semantic representation of the search request; and
generating, for display at the client device and for each one of the one or more documents, a graphical representation of at least a portion of each one of: the respective set of paragraphs, the respective set of sentences, and the respective set of words.
12 . The system of claim 11 , wherein the at least one processor is connected to the client device and has access to the trained model.
13 . The system of claim 11 , wherein the trained model is a machine learning (ML) model having been trained to generate and compare semantic representations of text objects.
14 . The system of claim 11 , wherein the text object comprises one of: a word, a sentence, a paragraph, and a document.
15 . The system of claim 11 , wherein the generating the semantic representation of the search request is based on the indication of the text object.
16 . The system of claim 11 , wherein the similarity condition with respect to the semantic representation of the search request is satisfied when each one of a plurality of semantic similarity scores obtained from a comparison of the semantic representation of the search request with each one of one or more document representations is indicative of a semantic similarity between the search request and a respective document of the one of more documents.
17 . The system of claim 16 , wherein each one of the plurality of semantic similarity scores is indicative of the semantic similarity between the search request and the respective document of the one of more documents when each one of the respective semantic similarity scores is above a threshold.
18 . The system of claim 17 , wherein the at least one processor is further configured for:
determining, based on a number of the one or more documents and the respective semantic similarity scores, the threshold.
19 . The system of claim 11 , wherein:
each one of the respective set of paragraphs satisfies the similarity condition with respect to the semantic representation of the search request when each one of a plurality of semantic similarity scores obtained from a comparison of the semantic representation of the search request with each one of the respective set of paragraphs is indicative of a paragraph semantic similarity between the search request and the respective set of paragraphs;
each one of the respective set of sentences satisfies the similarity condition with respect to the semantic representation of the search request when each one of a plurality of semantic similarity scores obtained from a comparison of the semantic representation of the search request with each one of the respective set of sentences is indicative of a sentence semantic similarity between the search request and the respective set of sentences; and
each one of the respective set of words satisfies the similarity condition with respect to the semantic representation of the search request when each one of a plurality of semantic similarity scores obtained from a comparison of the semantic representation of the search request with each one of the respective set of words is indicative of a word semantic similarity between the search request and the respective set of words.
20 . The system of claim 11 , wherein the graphical representation comprises a respective detailed view for each one of the one or more documents, the detailed view comprising the respective set of similar paragraphs, the respective set of similar sentences, and the respective set of similar words.