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Category: Semantic technologies (Page 5 of 72)

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.

Ontotext gets growth funding to meet demand for graph technology

May 26, 2022 /

Ontotext, an enterprise knowledge graph technology and semantic database engine provider, announced that Integral Venture Partners (Integral), a capital investment firm, announced this week that an Integral–led investment consortium has entered into a definitive agreement with our mother company Sirma Group Holding, to acquire Ontotext as a global supplier of a deep-tech enterprise software, operating in the graph databases space and the Artificial Intelligence market. The Integral-led international investment consortium also includes PortfoLion Capital Partners, the venture capital and private equity arm of OTP Bank, and Carpathian Partners, a specialized technology-focused investment platform based in London. The Consortium’s investment in excess of €30 million will be structured as a combination of a capital increase and a secondary share purchase. The transaction is not subject to any regulatory approvals and is expected to close by August 2022.

Supported by new capital, Ontotext will accelerate its international expansion and go-to-market operations, focusing on the US market. We will invest in further development of our vertical product stack — end-to-end solutions for specific industries starting with Life Sciences and Financial Services. Last but not least, we will further strengthen our position as global provider of knowledge graph technology.

https://www.ontotext.com

Relationship extraction with co-reference added to Finch for Text

May 19, 2022 /

Finch Computing, developers of real-time natural language processing solution Finch for Text, announced that it has added relationship extraction and co-references to the product. Relationship extraction gives users an ability to decipher relationships between entities, and co-reference enables words like “her” or “him” or “the leader” appearing in text to be resolved to a specific, named entity.

Finch for Text can now find important relationships between entities such as: Acquired-by, Co-Investor-with, Competitor-with, Customer-of, Director-of, Educated-at, Employer-of, Founder-of, Invested-in, Organization-Location, Owner-of, Partner-of, Person-Location, Relative-of, and Subsidiary-of. For companies and people in particular, understanding these connections helps users perform faster, richer and deeper analysis.

Entity co-reference refers to the ability to resolve otherwise obscure references to an entity – like her, him, the company, the product – to a disambiguated entity. The value of this capability is that it helps users understand all mentions of an entity even if that mention isn’t by name. It improves salience scores because the product can better gauge how much an article is about a given entity. It also improves sentiment scores with more mentions to analyze, and the same is true for relationship extraction – there are more relationships discovered because there are more mentions linked to an entity.

https://finchcomputing.com/2022/05/19/finch-computing-adds-spanish-german-language-support-to-its-finch-for-text-product-2/

Google Translate learns 24 new languages

May 11, 2022 /

From the Google Products Blog…

… today we’ve added 24 languages to Translate, now supporting a total of 133 used around the globe.

Over 300 million people speak these newly added languages — like Mizo, used by around 800,000 people in the far northeast of India, and Lingala, used by over 45 million people across Central Africa. As part of this update, Indigenous languages of the Americas (Quechua, Guarani and Aymara) and an English dialect (Sierra Leonean Krio) have also been added to Translate for the first time.

This is also a technical milestone for Google Translate. These are the first languages we’ve added using Zero-Shot Machine Translation, where a machine learning model only sees monolingual text — meaning, it learns to translate into another language without ever seeing an example. While this technology is impressive, it isn’t perfect. And we’ll keep improving these models to deliver the same experience you’re used to with a Spanish or German translation, for example. If you want to dig into the technical details, check out our Google AI blog post and research paper.

https://blog.google/products/translate/24-new-languages/

Expert.ai updates AI-based natural language processing platform

April 26, 2022 /

Expert.ai announced the new release of its platform combining symbolic, human-like comprehension and machine learning to turn language into data, analyze and understand complex documents, accelerate intelligent process automation and improve decision making. By extending core features and adding unique capabilities, such as out of the box knowledge models and connectors, the new release increases flexibility, simplifies integration and optimizes data pipelines to augment efficiency across every process that involves natural language (NL).

Specifically designed for natural language AI, the expert.ai platform leverages the combination of different AI techniques (machine learning and rule-based symbolic comprehension) with a simple and powerful authoring environment to support the full natural language processing workflow. It is based on the principle that no single natural language AI technique is a fit for every project. The new release includes:

  • ‘Smarter from the start’ knowledge models deliver NL applications to production faster with higher levels of business accuracy
  • Simplified deployment processes across multiple environments, including Azure
  • Easier integration, out of the box connectors
  • Enhanced natural language operations: provides the ability to include custom Python and Java scripts or third-party services for pre- or post-processing activities in NL workflow orchestrations.

https://www.expert.ai

AppTek launches new metadata-informed neural machine translation system

April 14, 2022 /

‍AppTek, a provider of Artificial Intelligence (AI) and Machine Learning (ML) for Automatic Speech Recognition (ASR), Neural Machine Translation (NMT), Natural Language Processing / Understanding (NLP/U) and Text-to-Speech (TTS) technologies, announced the release of its new neural machine translation system that incorporates metadata as inputs used to customize the MT output and empower localization professionals with more accurate user-influenced machine translations. Additionally, the company expanded its core machine translation platform to support hundreds of language and dialect pairs.

Traditionally, enterprises would need to train, deploy and maintain multiple MT systems to account for translation tasks that differ in aspects such as language, dialect, domain, topic, and more, at the risk of high deployment costs and overfitting models.

With AppTek’s new metadata informed NMT platform, enterprise customers can now access a single NMT system with multi-domain, multi-genre, multi-dialect content which increases the quality and adaptability of the system. By feeding additional metadata into the system, they gain more control of the MT output and can enable translators to simply “flip the switch” to the desired customized translation through relevant functionality in the user interface of the editing tools professionals work with.

http://www.apptek.com

Access Innovations announces Video/Audio to Text to Tagging solution for video transcript search

March 28, 2022 /

Access Innovations, Inc. announced Video/Audio to Text to Tagging (VATT), a solution that translates audio files to time stamped text transcripts for indexing, classifying, and enriching by Data Harmony Hub. Originally developed to improve search precision on training videos for a large chemical manufacturer, the new tagging capabilities can be used on any video or audio content from lectures, demonstrations, conferences, and more. Once metadata tagging is completed by Data Harmony Hub, a “point in time” search allows for users to find the precise time within the video/audio where the speaker or narrator discusses a specific topic, without wasting time browsing and scrolling through the entire video to find the information they need.

Organizations are generating video content and placing it on YouTube and other video aggregation service platforms. If transcripts are not available and searchable, the viewer is disappointed when they attempt to search a library of videos. In most cases, search is only available on the video title, the speaker or performer name, and possibly the date. With the video/audio to text to tagging solution, viewers enjoy a more robust search experience, reduce noise within the search results, and pinpoint topics and concepts of interest.

https://www.accessinn.com

Semantic Web Company and WAND Inc. announce partnership

March 15, 2022 /

WAND, Inc. announced a new partnership with Semantic Web Company. This partnership will blend the offerings of Semantic Web’s taxonomy management system with WAND’s taxonomies to accelerate client time to delivery. PoolParty opens up the use of WAND’s domain taxonomies to jump-start enterprise search, text analytics, business intelligence, artificial intelligence, knowledge graphs, and sentiment analysis. Based on a solid taxonomy, customers can invest more time and effort in customizing and thus fine-tuning their Knowledge Graph applications. The benefits of this new partnership include:

  • Informing A.I. Engines with a curated knowledge model
  • Speeding up time to delivery for projects
  • An extensibility to all domains of knowledge
  • Bundled pricing of WAND Taxonomies and PoolParty license

https://www.wandinc.com ■ https://semantic-web.com

Elastic releases Elastic 8.0

February 10, 2022 /

Elastic announced the general availability of Elastic 8.0 with enhancements across the Elastic Search Platform and its Enterprise Search, Observability, and Security solutions. Updates include native vector search, native support for modern natural language processing models, simplified data onboarding, and a streamlined security experience.

Native support for natural language processing (NLP) enables the use of custom or third-party PyTorch machine learning models directly in Elasticsearch. The addition of native NLP support with vector search enables users to perform inference within Elasticsearch, resulting in faster and more relevant search results. Customers can now leverage enhanced vector search capabilities, including native support for approximate nearest neighbor (ANN) search, to quickly perform queries on enormous data sets such as documents, images, and audio files.

Elastic native vector search extends technology commonly associated with searching for image and text content into the world of business data. Organizations can use vector search with NLP support to deliver faster, more relevant customer support information, improve shopping experiences, and enhance search accessibility by providing unique audio and visual search results. A simplified Elastic Cloud on AWS onboarding experience includes new integrations to speed data ingestion, including the new Elastic Serverless Forwarder.

https://www.elastic.co/blog/whats-new-elastic-8-0-0

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