Curated for content, computing, and digital experience professionals

Category: Semantic technologies (Page 1 of 63)

Our coverage of semantic technologies goes back to the early 90s when search engines focused on searching structured data in databases were looking to provide support for searching unstructured or semi-structured data. This early Gilbane Report, Document Query Languages – Why is it so Hard to Ask a Simple Question?, analyses the challenge back then.

Semantic technology is a broad topic that includes all natural language processing, as well as the semantic web, linked data processing, and knowledge graphs.


Expert.ai adds emotion analysis to natural language API

Expert.ai announced advanced features enhancing analysis capabilities through its cloud-based natural language (NL) API. The new extension addresses one of the biggest challenges artificial intelligence developers face in the NL ecosystem – extracting emotions in large-scale texts and identifying stylometric data driving a complete fingerprint of content.

The expert.ai NL API captures a range of 117 different traits, providing a rich emotional and behavioral taxonomy. Emotional Traits are categorized into 8 different groups (anger, fear, disgust, sadness, happiness, joy, nostalgia, shame…). Behavioral Traits are divided into 7 groups (sociality, action, openness, consciousness, ethics, indulgence and capability) and the API assigns 3 levels of polarity (low, fair, high) to further indicate the level of each trait extracted.

The emotions and traits extension can be useful to make media content categorization more effective by capturing new needs or advancing analytics by providing more detailed forecasting and enabling more effective recommendation tailoring for e-commerce. The expert.ai NL API writeprint extension performs a deep linguistic style analysis (or stylometric analysis) ranging from document readability and vocabulary richness to verb types and tenses, registers, sentence structure and grammar. Compare multiple documents to identify unique writing style and author invariants to streamline authorship analysis, establish the author of a specific text or isolate characteristics such as education level.

https://www.expert.ai

OmniIndex now in Oracle Cloud Marketplace

OmniIndex, a file analysis provider bringing analytics to unstructured data, announced that its solution is now available in the Oracle Cloud Marketplace, offering added value to Oracle Cloud customers.  This announcement confirms OmniIndex availability as a Software-as-a-Service via Oracle Cloud as well as being an Oracle for Startups member.

OmniIndex addresses all areas of unstructured data analytics: AI Contextual Awareness, AI Sentiment Analysis, Automatic Content Analysis and PII Alerting. It is a simple to implement SaaS solution with a powerful AI engine.

The Oracle Cloud Marketplace is a one-stop shop for Oracle customers seeking business applications and service providers offering unique business solutions, including those that extend Oracle Cloud Applications. Oracle Cloud  delivers enterprise-grade services at every level of the cloud technology stack including software as a service (SaaS), platform as a service (PaaS) and infrastructure as a service (IaaS). The Oracle Cloud Marketplace offers an intuitive user interface to browse and search for available applications and services, as well as user ratings and reviews to help customers determine the best business solutions for their organization. With its new automated application installation features, customers can easily deploy provider business applications from a centralized cloud interface. 

https://www.omniindex.io

Access Innovations launches Data Harmony Crescendo

Access Innovations, Inc. announced the launch of Data Harmony Crescendo, the cloud deployment of Data Harmony. Crescendo is a Platform as a Service (PaaS), available alongside the company’s Software as a Service (SaaS).

Data Harmony Crescendo helps clients index and process increasingly large amounts of data and deploy scalable, responsive, and self-managing services. This is achieved through centralized GIT driven project storage and version control, Docker containers for deployment and project loading, and Kubernetes clusters that are scalable and self-managing clusters capable of mostly administrating themselves. This allows for project development to be more agile: thesaurus features can be developed in sprints, development versions of the thesaurus can be deployed for testing before deployment, thesauri can be versioned and branched for different portions of the application, and project management is simplified at all levels. Docker containers allow for instant deployment and Kubernetes improves reliability, continuously monitors and manages containers, scales applications to handle changes in load, provides better use of infrastructure resources and helps reduce infrastructure requirements via autoscaling.

Crescendo forms a foundation for the infrastructure supporting semantics as a service. Access Innovations Labs helps clients and partners implementing semantic solutions, and takes on cutting edge projects to forward implementation of thesauri, taxonomies, and ontologies, supporting better search, discovery, and retrieval of information.

https://www.accessinn.com/2021/05/03/launch-of-data-harmony-crescendo/

AtScale supports Data Analysis Expressions (DAX)

AtScale, a provider of semantic layer solutions for modern business intelligence and data science teams, announced native support for Data Analysis Expressions (DAX). DAX is a formula expression language used in Analysis Services, Microsoft Power BI, and Power Pivot in Microsoft Excel. Native DAX support lets Power BI users connect to AtScale in live connection mode. Live connections provide fast access to AtScale’s semantic layer platform, for delivering and managing data access and quality across the diverse and complex data landscape in a cloud-first enterprise. The AtScale semantic layer creates a single point for data access and a central governance gateway, and bridges business users across data migrations. Key features:

  • Live Connection to Cloud Data Platforms – Power BI users can use AtScale to access up-to-date data without pre-aggregation or data engineering work.
  • Curated Data Models – These curated and governed data models can help to increase the quality of data analysis.
  • Impersonation & Single Sign-On (SSO) – With an appropriate data gateway configuration, Power BI users can connect using their preferred LDAP or Active Directory (AD) accounts.
  • Enhanced Performance – Power BI users can navigate metadata and use visualizations in their reports without requiring Power BI to translate DAX into a SQL dialect or other query language.
  • Seamless Integration with Power BI

https://www.atscale.com

DRUID and convedo partner in the UK and DACH region

DRUID, provider of specialists in conversational AI technologies, and convedo, provider of Intelligent Process Automation expertise, announced their collaboration to deliver the DRUID Chatbot Authoring Platform in the UK and DACH region, (Germany (D), Austria (A), and Switzerland (CH)). convedo helps the world’s organizations succeed with Intelligent Process Automation using best-of-breed platforms and will now introduce conversational artificial intelligence (AI) technology to more companies from various industries. DRUID provides a platform for designing, developing, and integrating a chatbot tailored to specific business needs and objectives.

DRUID is an AI-driven, no-code chatbot authoring platform that has a robust integration capability into back-end systems. The natural language processing technology included in the platform supports over 45 languages and offers more than 500 pre-built conversational AI templates covering business scenarios across multiple industries and roles. Moreover, the native connector with UiPath adds conversational capabilities to the hyper-automation platform.

https://www.druidai.com/druid-ai-partners-convedo-automation-uk-dach/ ▪︎ https://www.convedo.com

Google DocAI now generally available

Google announced the availability of the latest releases of their Document (Doc) AI platform, Lending DocAI and Procurement DocAI. Most companies are still manually entering data and reliant on guesswork to make sense of it all as the volume and variety of data explodes. Organizations are also leaving heaps of value on the table in the form of new and better customer experiences that can be unlocked with artificial intelligence (AI) applied to documents. The DocAI platform, based on Google’s AI expertise, bring powerful and useful solutions to these challenges. Under the hood are Google’s technologies:

  • Computer vision (including OCR) and Natural Language Processing (NLP) that creates pre-trained models for high-value, high-volume documents.
  • Google Knowledge Graph to validate and enhance the fields in your documents.
  • Training and creation of your own custom document models.
  • Human interaction with AI to ensure accuracy where needed.

The new specialized parsers for Lending and Procurement DocAI can be used alongside our existing AutoML Text & Document Classification and AutoML Document Extraction services. Next up is the general availability of Human-in-the-Loop AI, a new DocAI feature that will help companies achieve higher document processing accuracy with the assurance of human review.

https://cloud.google.com/blog/products/ai-machine-learning/get-more-value-from-your-documents-with-docai-and-industry-solutions

Sinequa launches Intelligent Search Platform on Microsoft Azure

Sinequa, a provider of Intelligent Enterprise Search, announced the launch of Sinequa for Microsoft Azure to better serve customers who want to take advantage of Azure and its global reach. Organizations that use Azure can now access Sinequa’s enhanced version of a self-managed Intelligent Search platform.

Sinequa for Azure enables digital workers to stop sifting for information across Enterprise applications and brings the knowledge and insight to the users no matter the source, format, language, or location. Integrated with Microsoft 365 (Microsoft Teams, Microsoft SharePoint, etc.), Sinequa also seamlessly extracts valuable information from applications such as Salesforce, Box, Dropbox, OpenText, Documentum, file shares, databases, and other data sources, by leveraging a portfolio of over 200 out-of-the-box connectors.

Sinequa for Azure integrates Azure Cognitive Services to enable organizations to ingest all of their enterprise data sources, transform that data into searchable information, and enable users to get precise insights to natural language queries. Sinequa for Azure benefits include: reduced architecture costs, faster, indexing, more secure platform; easier, quicker deployment, optimized for Azure, environmentally friendly. Sinequa for Azure is now available in the Azure Marketplace.

https://www.sinequa.com/intelligent-enterprise-search-optimized-for-azure/

Ontotext Platform 3.4 brings better search and aggregation in knowledge graphs

Ontotext announced Ontotext Platform 3.4 for better search and aggregation in knowledge graphs. Key to the Ontotext Platform is the declarative approach for access and management of large-scale knowledge graphs (KG). This allows engineering teams to define specific GraphQL interfaces to read and write data over parts of a knowledge graph and let the Platform implement an efficient translation of GraphQL to SPARQL.

Ontotext Platform 3.4 combines GraphDB, Elasticsearch and GraphQL by enabling the definition, automatic synchronization and querying of indices to boost the performance of specific queries. The Workbench front-end tool of the Platform features a new generic search interface for KG exploration and navigation. The new version of the Semantic Object service delivers better performance to execute big and data-intensive GraphQL queries on top of GraphDB.

The new Semantic Search Service enables software engineers to easily accomplish some of the capabilities over a knowledge graph that are most required by SMEs such as Full-text Search (FTS), Auto-complete/typeahead (related concepts and controlled vocabulary), Auto-suggest (related keywords and phrases), Faceted search, complex dashboards using different statistical and/or bucket aggregations, etc. The provided GraphQL endpoint will enable users not only to search in the data but also to retrieve the data for the result list directly from Elasticsearch.

https://www.ontotext.com

« Older posts

© 2021 The Gilbane Advisor

Theme by Anders NorenUp ↑