Are you wondering how best to formulate your queries? Sinequa supports multiple query types, including freeform text, advanced criteria, and fielded search. Employees can ask “native” questions and get suggestions for the best query type to use. Sinequa also handles multilingual search and natively applies morphosyntactic analysis, phonetization, spelling corrections, and expansions out-of-the-box.
Natural language processing is the science behind machine comprehension. If you’re new to the concept or looking for an overview of what it is and how it’s used, then this guide is for you.
NLP can be both leveraged at search and indexing time, further enhancing the employee’s search experience.
Sinequa automatically detects the language used in the query and performs a syntactic analysis of the text for automatic spell checking and phonetic correction of the query. It also includes query auto-completion, query suggestion and similar document suggestion. The behavior of these features can be configured and tailored to specific applications, including the use of custom dictionaries as desired.
Query intent detection is the art of providing the right information to the right user in its particular context.
Sinequa’s insight engine finds and presents the right information to make it directly actionable instead of just searching for the most relevant document according to pure information retrieval techniques. Two technologies are combined here to make this happen:
An intuitive interface that employees can use to handle complex queries, including inline metadata search.
While complex advanced search forms are less and less in use nowadays, sophisticated applications may be required to filter the answers by additional metadata criteria. To avoid overcomplicating the search interface, an employee may use the simple search box to type complex queries that include multiple criteria applying to metadata. The syntax is straight forward assuming the employee is familiar with the "from:" "to:" or "site:" already in use with major email systems or public search engines.
Run complex searches by filling up customizable advanced search forms.
An advanced search is easily set up by adding as many search criteria as needed by the use-case and combined at will. Sources, formats, dates range, authors, and any custom metadata can be added within advanced forms, along with rich and intuitive features like multi-selection, sliders, exclusions, etc.
Make your search more intuitive and contextually relevant, thanks to the "Auto-Suggest" functionality.
BLOG - For many enterprises, the solution appears to mean investing in advanced search capabilities. But the most common approach is to expand basic search by adding on advanced features. Over the long term, that approach has built-in limitations. Eventually, you're bound to run up against the law of diminishing returns.
BLOG - Leveraging Machine Learning algorithms and advanced natural language processing (NLP), cognitive search and analytics solutions enable customers to embark on ambitious Big Data projects with the opportunity to extract relevant information from the volumes of content they retain.
Most of the world’s content is not on Google: Some 80% of it is housed behind firewalls at the world’s companies and organizations. Every day, your employees are generating new project ideas, performing R&D, executing financial transactions, serving customers, generating data in business applications and databases, and much, much more – structured data that may or may not be available for search, given its format or where it is stored.