Abstract: Various embodiments of the present disclosure provide model-based domain-aware autocomplete techniques for generating autocomplete suggestions in a complex search domain. Example embodiments are configured to generate, using a domain-aware autocomplete model, a label for an autocomplete suggestion based on a set of keywords within an autocomplete suggestion training dataset associated with a target domain source. Example embodiments are also configured to generate, using a weak-labeling model, an updated label for the autocomplete suggestion by decorrelating the set of keywords from the label. Example embodiments are also configured to generate, using a sentence classification model, a category for the autocomplete suggestion based on the updated label. Example embodiments are also configured to, using the domain-aware autocomplete model, generate a suggestion-category pair (SCP) based on the autocomplete suggestion and the category for the autocomplete suggestion.

Abstract: Various embodiments of the present disclosure provide an interactive map-based visualization system related to multi-channel search for search domains to improve upon traditional search resolutions within such domains. The techniques may include receiving a user interface request that comprises (i) character-level text input related to a search query via a user interface of a user device and (ii) filter metadata for a user identifier associated with the user interface request, generating a set of query result data objects for the user interface request by correlating the character-level text input to at least one domain knowledge profile, and generating a set of filtered query result data objects for the user interface request by filtering the set of query result data objects using the filter metadata. In some examples, the techniques may include initiating a rendering of a set of selectable graphical element options that are correlated to a real-time map visualization.

Abstract: Various embodiments of the present disclosure provide query processing techniques for resolving queries in a complex search domain to improve upon traditional search resolutions within such domains. The techniques may include generating a keyword and an embedding representation for an agnostic search query. The keyword representation may be compared against source text attributes within one or more domain channels to generate a plurality of keyword similarity scores between the search query and features within a search domain. The embedding representation may be compared against source embedding attributes within the one or more domain channels to generate a plurality of embedding similarity scores between the search query and the features within the search domain. The keyword and embedding similarity scores may be aggregated to generate aggregated similarity scores for identifying an intermediate query resolution for the search query. The intermediate query resolution may be leveraged to resolve the query.

Abstract: Various embodiments of the present disclosure provide model-based domain-aware autocomplete techniques for generating autocomplete suggestions in a complex search domain. Example embodiments are configured to generate, using a domain-aware autocomplete model, a label for an autocomplete suggestion based on a set of keywords within an autocomplete suggestion training dataset associated with a target domain source. Example embodiments are also configured to generate, using a weak-labeling model, an updated label for the autocomplete suggestion by decorrelating the set of keywords from the label. Example embodiments are also configured to generate, using a sentence classification model, a category for the autocomplete suggestion based on the updated label. Example embodiments are also configured to, using the domain-aware autocomplete model, generate a suggestion-category pair (SCP) based on the autocomplete suggestion and the category for the autocomplete suggestion.

Abstract: Various embodiments of the present disclosure provide model-based domain-aware autocomplete techniques for generating autocomplete suggestions in a complex search domain. Example embodiments are configured to generate, using a domain-aware autocomplete model, a label for an autocomplete suggestion based on a set of keywords within an autocomplete suggestion training dataset associated with a target domain source. Example embodiments are also configured to generate, using a weak-labeling model, an updated label for the autocomplete suggestion by decorrelating the set of keywords from the label. Example embodiments are also configured to generate, using a sentence classification model, a category for the autocomplete suggestion based on the updated label. Example embodiments are also configured to, using the domain-aware autocomplete model, generate a suggestion-category pair (SCP) based on the autocomplete suggestion and the category for the autocomplete suggestion.