AnzoGraph DB is now a Graph Database that Supports Geospatial
Use new Geospatial and GeoSPARQL functionality in AnzoGraph DB to develop large scale location intelligence and geospatial applications along-side rich data-analytics using SPARQL* and RDF*.
How Gunosy built a comment feature in News Pass using Amazon Neptune | Amazon Web Services
tech, Gunosy Ads, and the Gunosy Ad Network. The information curation service collects and distributes information sourced from the vast amount of information on the internet, filtered by specific criteria. Gunosy uses algorithms to collect and organize information to deliver the right information to the right people.” News Pass is a free applicatio
Structuring Unstructured Content: The Power of Knowledge Graphs and Content Deconstruction
Unstructured content is ubiquitous in today’s business environment. In fact, the IDC estimates that 80% of the world’s data will be unstructured by 2025, with many organizations already at that volume. Every organization possesses libraries, shared drives, and content management systems full of unstructured data contained in Word documents, power points, PDFs, and more. Documents like these often contain pieces of information that are critical to business operations, but these “nuggets” of information can be difficult to find when they’re buried within lengthy volumes of text. For example, legal teams may need information that is hidden in process and policy documents, and call center employees might require fast access to information in product guides. Users search for and use the information found in unstructured content all the time, but its management and retrieval can be quite challenging when content is long, text heavy, and has few descriptive attributes (metada
Oct 25, 2019 · 11 min readThere is an unreasonable amount of information that can be extracted from what people publicly say on the internet. At Heuritech we use this information to better understand what people want, which products they like and why. This post explains from a scientific point of view what is Knowledge extraction and details a few recent methods on how to do it.What is knowledge extraction?Highly structured databases make it easy to reason with and can be used for inference. For example in WikiData or YAGO, entities are isolated and linked together with relations. However, most of the human knowledge expressions take the form of unstructured texts, from which it is very hard to reason and get wisdom. Consider the example here:The raw text on the left contains a lot of useful information in an unstructured way, such as birthday, nationality, activity. Extracting those information corresponds to a challenging field in Natural Language Processing, which may require
constructed reports, that is easy, but as they become long, then things get really difficult. Thankfully there are a whole bunch of tools that are now becoming available that allow for the extraction of insights.The tools are possible owing to the advancements in natural language processing — the use of computational techniques and models to analyse natural language — language as it is used around us — in the documents, in voice, in chats. The explosion of content generated, and especially Wikipedia — has made various advancements possible. Thanks to Wikipedia, which contains topics arranged in a structured manner, and thanks to the effort put into translation by Go
Facebook Search Results Now Include Wikipedia Knowledge Panels
Facebook appears to be testing the addition of Wikipedia knowledge panels in search results, according to reports from multiple users.Based on the screenshots shared on Twitter, this feature is reminiscent of Google’s integration with Wikipedia.Here’s an example that was spotted a few days ago:New? Facebook shows Wikipedia snippits in search resultsh/t @jc_zijl pic.twitter.com/zcbQJmauhE— Matt Navarra | 🚨 #StayAtHome (@MattNavarra) June 9, 2020Just like in Google’s search results, the Wikipedia knowledge box in Facebook search shows key details about the entity being searched for.You’ll also notice there’s a lone Instagram link, which is a stark contrast to Google’s search results containing links to all popular social media profiles.Unlike Google’s knowledge panels, which link to a number of domains where people can learn more about a entity, Facebook is trying to keep people within the Facebook ecosystem as much as possible.Here’s another example that looks
Cambridge Semantics Recognized for Leadership in Use of OLAP Knowledge Graph Technology for Accelerated Data Integration
This week, Cambridge Semantics was named a Leader in The Forrester Wave™: Enterprise Data Fabric, Q2 2020, and we could not be more delighted. Forrester used 25 criteria to evaluate the 15 most significant enterprise data fabric vendors to show how each vendors' platforms measure up in their ability to accelerate data integration, minimize the complexity of data management, and quickly deliver use cases. Cambridge Semantics received top scores for Vision, Road Map, Solution Awareness, Data Preparation, Data Integration, Data Catalog, and Data Processing. This evaluation, we believe, validates Cambridge Semantics' breakthrough approach to the data fabric, and reflects the feedback we are hearing from customers and partners using our solution to integrate and manage large volumes of data quickly and at scale.
This story was originally published on InsideBigData .Knowledge graphs are one of the most important technologies of the 2020s. Gartner predicted that the applications of graph processing and graph databases will grow at 100% annually over the next few years.Over the last two decades, this technology was adopted mostly by engineers and ontologists, hence the majority of knowledge graph tools were designed for the users with advanced programming skills.In 1900, 40% of the population was involved in farming.Today it’s 1%. Coding is the modern day “farming” as only 0.5% of the world’s population knows how to code.NoCode brings equal opportunities to talent of all trades.Let’s just imagine, what impact this could have if the majority of world’s population was able to take advantage of cutting edge technologies to solve top of mind problems.Empowering top talent with NoCode approachEngineering and programming are important skills but only in the right context, and only for
Listen, SQL and relational databases people: The knowledge revolution has reached the SQL world and it will change it forever.
>)You may have read that companies such as Amazon, Facebook, Microsoft, JPMorgan and Bank of America have made large investments to develop their own proprietary knowledge graphs, to make “strategic use of data and extend business boundaries[1]”.How is this relevant to the “SQL World”?What does this have to do with you, the SQL/relational database professional? Why should you care that there is a new world of databases that is alien to most relational databases experts and users?For the near future maybe you shouldn’t care. After all, about 80% of the database infrastructure in the world is relational, so for you SQL is a sure bet.But wait, here’s big data, ever growing big data. Big data is complex, it has variety and it is difficult to
Memorizing vs. Understanding (read: Data vs. Knowledge)
up the value of e anytime I need it (figure 1);Figure 1. A data dictionary with key and value of arithmetic expressions.(ii) if I do not have that option then the only other alternative to get the value of e is to actually compute the arithmetic expression and get the corresponding value. The first method, let’s call it the data/memorization method, which does not require me to know how to compute e while the second does. That is, in using the second method I (or the computer!) must know the procedures of addition and multiplication, shown in figure 2 below (where Succ is the ‘successor’ function that returns the next natural number).Figure 2. Theoretical definition of the procedures/functions of addition and multip
Can knowledge graphs help untangle the RegTech data management puzzle
based Technology Enables Companies in the Financial Sector to Quickly and Efficiently Integrate and Analyze the Explosion of Disparate Data from RegulatorsOver the past decade, the advance of digital innovation combined with the growing number of regulatory guidelines in all jurisdictions has sped up the rise of Regulatory Technology, or RegTech for short. Originally, its main application was to enhance regulatory processes in the Financial sector, but nowadays it is expanding more and more in to any regulated business. A good sign that this technology is steadily going mainstream is also the fact that more and more regulatory bodies are supporting RegTech development and implementation.According to a September 2019 report from Juniper Research, the value of global spending on RegTech is expected to jump to more than US $127 billion by 2024, up from US$25 billion spent in 2019. Automation in Know Your Customer (KYC) processes and background checks are set to be so
The Art of Compromise — finding an optimal Knowledge Graph solution
time.Therefore, we have recognised that building a “Talent Knowledge Graph” will allow us to effectively operate in our domain as well as to fully unlock the predictive power of artificial intelligence and provide unique insights from our heterogeneous data sources.After Google’s reveal of its Knowledge Graph platform in 2012, the term has been rapidly growing in popularit
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