• Blog
  • Informational

Semantic Search: The Paradigm Shift from Results to Relationships

April 27, 2016 7 mins. read Teodora Petkova

Searching in big data

“Sorry, no content matched your criteria” is probably one of the most frustrating messages we can get after a search. Especially, nowadays when more and more of the world’s information is supposed to be at our fingertips, seemingly a click away. If we look behind that, though, we’ll see an important reminder from today’s data-driven world:

The potential of data for knowledge discovery is only as big as the capacity to intelligently search through these data. Click To Tweet

Understanding Semantic Search Through a Verse From Antiquity

Semantic search is what opens the door for such intelligent information retrieval.

When referring to machines, the term ‘intelligent’ raises not just an eyebrow. The controversy is immediately up when we start discussing if we want machines to be able to understand the meaning of content.

However, it subsides the moment we are faced with a pressing need to find the nearest pharmacy or speed up our research project. In these cases, (not surprisingly) we are happy to use an elaborate computational process to sift through data and get to the most relevant results as quickly as possible.

Semantic search does exactly that. It is an approach to querying data that seeks to understand (i.e., to compute) the intent and the context around a query in order to retrieve the most pertinent resources, related to the particular information request.

To grasp the semantic approach to search, it is useful to look a couple of millennia back where an unexpected perspective on the process of understanding emerges.

Launched on the void, assail it not as yet
With keen-edged sickle, but let the leaves alone
Be culled with clip of fingers here and there.

Verg. G. 2.366

The verb “cull” in the last verse is a translation of the Latin verb “intellegere”. This Latin word literally means “to choose from”, it is formed from inter ‘between’ and legere ‘choose’. With time intellegere came to denote “understand” and to further grow more elaborate meanings. Its present participle (intelligens, i.e., discerning) is the origin of the word intelligent.

That explained, the verse above can be read as another reminder, this time from the distant past, restating the fundamentals of understanding: the ability to pick from.

Bye Bye Keywords, Hello Networks of Relationships

Networks of Relationships

In simple terms, the ability to pick from is our capacity to discern noise from actionable information that moves us forward on our quest for finding relevant knowledge and, ultimately, answers. What the semantic approach to information retrieval does is enhance this capacity by utilizing the analytical powers of computers to dig huge amounts of data and surface their interconnections for us.

Neither text nor any type of content can be exhaustively defined by their exact textual representation. In both cases, it’s more about a fabric of relationships. Not just the mere sum of exact words and phrases but a network of entities connected in a so-called knowledge graph.This term is gaining more and more popularity thanks to Google who first adopted it. But what is important is that is by analyzing the relational aspects of these entities that Semantic Search is able to address complex queries, foster knowledge discovery and take information retrieval to the next level. In other words, from a list of results solely based on keyword matching to a set of connections, pertinent to the intent and the context of the specific query.

Leveraging Semantic Technology and, more specifically, data represented in RDF and organized in formal collections (ontologies) of related entities, Semantic Search turns the process of looking for information from “dull” term matching into asking questions and getting answers.

By definition, Semantic Search reaches out beyond keywords and seeks to understand the semantics of the search query. It improves search accuracy by looking at both the data and their connections. Instead of more links, which are only a single kind of a relationship, the algorithm presents you with a networked view of relationships you might not be aware of.

Semantic Search Across the Web: The Inevitable Shift

In his book Google Semantic Search (op. cit., p. 13), author David Amerland writes:

Search is key to making the Web useful, creating order out of its chaotic data, and making it navigable.

The adoption of Semantic Technology is inevitable for their potential to model real-world complexity and manage resources and their interrelations in a machine-readable format. In contrast to search based on the occurrence of words in documents, querying interconnected pieces of data whose chain of relationships can be followed allows for deeper and broader search experience.

On the Web, Semantic Search profoundly changes the landscape of SERPs. Google, Bing, Yahoo! and Yandex, to mention the major search engines, constantly optimize their algorithms, as to be able to return richer results to search queries.

In their effort to enable Web-scale exchange of structured data through Schema.org (a collaborative, community activity creating, maintaining and promoting schemas for structured data on the Internet), search engines also enable the publishing of more and more Semantic Web data. This, in turn, makes Semantic Search more precise and reliable. The more data an algorithm is presented with, the better the chances it can accurately assess and verify them.

Put shortly, Semantic Search across the Web becomes smarter and its potential to satiate the need for relevant results, save time and provide a better user experience grows. And this is what keeps search engines in business.

But the same applies for enterprise Semantic Search. Incrementally, more and more companies realize the dire need for better information retrieval systems and more agile ways of managing knowledge across their structures.

Needed Data

Enterprise Semantic Search: Benefits and Challenges

Within organizations and closed enterprise systems, Semantic Search implementation translates into efficient enterprise content usage. A Semantic Search built on top of an existing content management system brings new dimensions to extracting usable information out of huge amounts of heterogeneous data. This solves one of the big problems many organizations face: the massive volumes of dark data, which is hard to discover by content creators.

Enabling the navigation of semantically integrated data, Semantic Search enables discovery of hidden relationships and information gathered beyond keywords, and saves hours of fishing disparate data scattered across multiple resources. Click To Tweet

Despite the advantages, though, Semantic Technology gains traction very slowly and incorporating Semantic Search is still a challenge for many organizations. Businesses are still a bit short-sighted to the opportunities interlinking their data, content and the Web can open for them. Too focused on the short-term benefits, they are still hesitant about what this technology can buy them.

The Quest for Meaning

The good news is that major Web search engines and larger organizations are already paving the road to a more meaningful Web and more efficient enterprise content management systems, thus bringing good Semantic Search practices for others to take advantage of.

Steadily, the algorithms that understand the semantics of our searches are becoming smarter. With a smarter and more precise information retrieval approach, more correlations are being found, more clues are being presented, ultimately, more breakthroughs are being made.

Semantic Search proves to be not only a tool for exploring and retrieving information but also a powerful way to ‘cull’ knowledge out of data and to really help us put the world’s information at our fingertips.

Want to learn more and see some examples?

White paper Text Analytics for Enterprise Use
White Paper: Text Analytics for Enterprise Use
Use the power of text analytics for your enterprise

Download Now



Article's content

Marketing Expert at Ontotext

Teodora is a philologist fascinated by the metamorphoses of text on the Web. Curious about our networked lives, she explores how the Semantic Web vision unfolds, transforming the possibilities of the written word. From 2022 on, Teodora helps with the creation and curation of the Ontotext knowledge graph to foster information ecology out of marketing content that will enable relevant user experiences across Ontotext's universe.

GraphDB in Action: Smells Like Semantics Spirit

Read about a project called Odeuropa and a number of exciting applications delivered by it with our RDF graph database humming behind them

KGF 2023: Bikes To The Moon, Datastrophies, Abstract Art And A Knowledge Graph Forum To Embrace Them All

Read about this year’s Knowledge Graph Forum – a space where Ontotext and partners presented smart and linked ways to tame and thrive on complexity, rather than be drowned by it

Do Large Language Models Dream of Knowledge Graphs – Impressions from Day 2 At SEMANTiCS 2023

Read our report from Day 2 of SEMANTiCS 2023 to find out if ChatGPT is the killer app for the Semantic Web, how do we tame the genie of LLMs for Healthcare and more

Can LLMs Become Knowledgeable – Impressions from Day 1 At SEMANTiCS 2023

Read about the interplay between LLMs & KGs and how business and academia tackle them in our report from Day 1 at SEMANTiCS 2023

It’s Time We Give Each Other More Data Spaces: Impressions from the Pre-conference Day at SEMANTiCS 2023

Read about SEMANTiCS pre-conference day, which covered the topics of interoperability, ESG data, knowledge engineering, scholarly communication, and academia & industry collaboration.

GraphDB in Action: Navigating Knowledge About Living Spaces, Cyber-physical Environments and Skies 

Read about three inspiring GraphDB-powered use cases of connecting data in a meaningful way to enable smart buildings, interoperable design engineering and ontology-based air-traffic control

Your Knowledge Graph Journey In Three Simple Steps

A bird’s eye view on where to start in building a knowledge graph solution to help your business excel in a data-driven market

GraphDB in Action: Putting the Most Reliable RDF Database to Work for Better Human-machine Interaction

Read about the world of academia research projects that use GraphDB to meet the challenges of heterogeneous data across various domains

Knowledge Graphs for Retail – Connecting People, Products and Platforms

Read about how knowledge graphs can serve the retail industry’s growing need to connect, manage and utilize data efficiently, aligning it in a collaborative data ecosystem

Data Wants To Be Truly Sovereign: Designing Data Spaces with Linked Data Principles In Mind

Read about what data spaces are and how semantic technologies and Linked Data can make them a stronger and safer mechanism for commercial data exchange

GraphDB in Action: Powering State-of-the-Art Research

Read about how academia research projects use GraphDB to power innovative solutions to challenges in the fields of Accounting, Healthcare and Cultural Heritage

KGF22: Knowledge Graphs and The Not So Quiet Cognitive Revolution

Read about Ontotext’s KGF22 days dedicated to stories about knowledge graphs in the domains of Industry, Healthcare & Life Sciences and Financial Services

KGF22: Wittgenstein, Developers Empathy and Other Semantic Data Considerations

Read about our event report from Ontotext’s Knowledge Graph Forum 2022, highlighting expert insight on building knowledge graphs and designing enterprise-grade solutions with semantic technologies.

A Little SEMANTiCS Goes A Long Way

Take a sneak peek at some of the keynote speeches and tutorials throughout SEMANTiCS 2022

It Takes A Village To Raise An Enterprise Knowledge Graph

Read about the design processes behind crafting knowledge-graph enabled solutions and explore some of the stories of our partners.

Smart Buildings Are Built of Smart Data: Knowledge Graphs for Building Automation Systems

Read about how knowledge graphs offer a sustainable solution for harnessing and making sense of heterogeneous data in the building automation industry.

Metadata Moves: Knowledge Graph Technology for Logistics

Read about how the world of metadata humming behind the logistics and other supply chain processes can benefit from using knowledge graph technology.

Electrical Standards, Smart Grids and Your Air Conditioner

Read about how applying Linked Data principles and semantic technology to electricity data can make for a more efficient, reliable and sustainable electricity market.

The Semantic Web: 20 Years And a Handful of Enterprise Knowledge Graphs Later

Read about how the Semantic Web vision reincarnated in thousands of Linked Open Data datasets and millions of Schema.org tagged webpages. And how it enables knowledge graphs to smarten up enterprises data.

Metadata is Like Packaging: Seeing Beyond the Library Card Metaphor

Read about what metadata is, why it is important and how it can enhance the ways information flows across the enterprise.

From Fragmented Data to a Comprehensive Knowledge Graph: The Case for Building an R&D Repository

Read about how enterprise knowledge graphs can unlock meaning and thus create a smart future-proof living repository of scientific data and its relationships.

Texts Without Pages: Advancing Text Analytics with Content Enrichment

Read about how text analytics can be brought forward with content enrichment processes for better text authoring, delivery and navigation.

A Shield Built of Connected Data: Knowledge Graphs Meet Cybersecurity

Read about how a knowledge graph can help organizations stay vigilant of the increasing number of cyber threats, keeping malicious attacks at bay with the help of semantics.

Digital Twins: If It Sounds Like Cyberpunk, It’s Because It Is

Read about what digital twins are, what makes them attractive to companies and how digital twins relate to semantic technology and enable organizations to design, simulate and validate various scenarios virtually.

Eating the Knowledge Soup, Literally

Read about the fluid essence of knowledge and the capability of knowledge graphs to power an information-rich platform of diverse facts about anything, a broccoli soup included.

If Curiosity Cabinets Were Knowledge Graphs

Read about why and how knowledge graph technology can help build networks of interwoven digital objects in the world of cultural heritage.

On the Hunt for Patterns: from Hippocrates to Supercomputers

Read about the ExaMode project that will help medical professional use the power of supercomputers and knowledge graphs for more efficient patient care through data-driven diagnoses.

Crafting a Knowledge Graph: The Semantic Data Modeling Way

Read about how to build a knowledge graph the semantic data modeling way in 10 steps, provided by our knowledge graph technology experts.

A Graphful of Investment Opportunities

Read about the story of an algorithm that mines data to narrow down opportunities for investing.

Okay, You Got a Knowledge Graph Built with Semantic Technology… And Now What?

Read about how knowledge management can be made smarter using a knowledge graph built with semantic technology.

If Johnny Mnemonic Smuggled Linked Data

Read about how semantic technology and Linked Data can help enterprises benefit from smart data management and retrieval practices.

Data, Databases and Deeds: A SPARQL Query to the Rescue

Read about why and how SPARQL queries make for a better search in diverse datasets across an organization in an integrated way.

Semantic Technology and the Way We See the World

Read about how semantic technology can help you set the wheels for many processes related to еfficient data management and governance.

Telling Stories with an RDF Database

Read about the opportunities for authoring and publishing workflows opened by an RDF triplestore.

The Power of URI or Why Odysseus Called Himself Nobody

Read about URI and its power to enable the sharing and reuse of machine-readable data with minimum integration costs.

From Cultivating Nature to Cultivating Data: Semantic Technology and Viticulture

Learn how the potential that Big Data streams bring to grape and wine production can be harnessed with the right kind of technology.

The Knowledge Graph and the Enterprise

Read about the knowledge graph and about how many enterprises are already embracing the idea of benefiting from it.

It Don’t Mean a Thing If It Ain’t Got Semantics

Learn how you can turn data pieces into actionable knowledge and data-driven decisions with an RDF database.

The Bounties of Semantic Data Integration for the Enterprise

Learn about the potential semantic data integration carries for piecing massive amounts of data together.

Here’s a Graph, Go Figure! Coupling Text Analytics with a Knowledge Graph

Learn why and how a Knowledge Graph boosts significantly Text Analytics processes and practices and makes text work for us in a more meaningful way.

Cognitive Computing: Let’s Play an Awareness Game

Read about the new breed of computing is emerging before our eyes – cognitive computing and join us in our Awareness Game.

Machine Learning and Our (Insatiable) Penchant for Making Things Smarter

Read about how machines can be of great help with many tasks where fast and error-free computation over big amounts of data are required.

Staying In the Vanguard of Digital Transformation with Open Data

Learn about Open Data and its potential to be part of smart solutions to data problems and innovative products and services.

Whose Meaning? Which Ontology?

Read about how ontologies open up opportunities for a new class of tools to power information consumption and knowledge management.

Shiny Happy Data: A Praise for RDF

Learn how to choose the right solution for working with your data the conceptual framework of “happy connected people”.

Enterprise Metadata Matters: From Having Data to Acting Upon Them

Learn more about the importance of being metadata-driven today in our latest SlideShare presentation.

Data Daiquiri: The Power of Mixing Data

Learn how companies can tap into the power of the data coming their way by integrating the huge data flows with their proprietary data.

Migrating to GraphDB: Your Why and How in 20 slides

Learn about the steps you need to migrate your data to GraphDB to use it as a smart brain on top of your legacy systems.

Got meaning? Or Why an RDF Graph Database Is Good for Making Sense of Your Data

Read about how you can create systems capable of discovering relationships and detecting patterns within all kinds of data.

Brains Armored with Smart Data

Read our thoughts rising from questions such as “Will Giant Brains Rule the World?” and “Can a mechanical brain replace you?”

One Step Closer to Intertwingularity: Semantic Metadata

Learn about how semantic metadata allows us to add granularity to an object, interlink it to other objects and make it easy to search.

Exceptional User Experiences with Meaningful Content NOW

Content enrichment and semantic web technologies are key to efficient content management. Learn why and see these technologies in action.

Semantic Information Extraction: From Data Bits to Knowledge Bytes

Learn about semantic information extraction and how it pulls out meaningful data from textual sources, ready to be leveraged for insights, decisions and actions.

Weaving Data Into Texts: The Value of Semantic Annotation

Read about how semantic annotation links certain words to context and references that can be processed by an algorithm.

Exploring Linked Open Data with FactForge

Learn about FactForge and how you can turn the opportunities that data flows on the web can pour into our business into a real experience.

What is GraphDB and how can it help you run a smart data-driven business?

Learn about GraphDB in a simple and easy to understand way and see what Ontotext’s semantic graph database has to do with pasta making.

Linked Data for Libraries: Our New Librarians

Learn how semantic technologies can bring audiences back to libraries and make library archives and collections visible and accessible.

Working with Data Just Got Easier: Converting Tabular Data into RDF Within GraphDB

Read about OntoRefine – a new tool that allows you to do many ETL (extract, transform and load) tasks over tabular data.

GraphDB: Answers for Kids of All Ages

Read about how GraphDB can help you clean up messes of data (just like your room) – whether you are a kid or not.

The Knowledge Discovery Quest

Learn how by joining the dots, semantic search enhances the way we look for clues and compare correlations on our knowledge discovery quest.

Connectivity, Open Data and A Bag of Chips

Learn how LOD’s connectivity allows data to be shared seamlessly, used and reused freely. As simple as a bag of chips.

Data Integration: Joining the Data Pieces of Your Business Puzzle

Learn how to use information interconnectedness to integrate, interpret and ultimately make sense of data.

Cooking Up the Semantic Web

Read about the Semantic Web and what it takes to reach its potential and evolve from a Web of Documents to a Web of Data.

Semantic Search: The Paradigm Shift from Results to Relationships

Read about semantic search and how it takes information retrieval to the next level and puts information at our fingertips.

A Web of People and Machines: W3C Semantic Web Standards

Learn how and why Semantic Web Standards are to serve the Web of Data for better collaboration between people through computers.

Thinking Outside the Table

Learn how to manage highly connected data, working with complex queries and having readily available relationships, without the need to express them explicitly.

Our Networked Lives, Publishing and Semantic Technologies

Read about how semantic technology helps publishing handle data in an interconnected way, attaching machine-processable and readable meaning to them.

Why Graph Databases Make a Better Home for Interconnected Data Than the Relational Databases?

Read about how you can turn data into a resource, easily accessed and effectively used across the organization with a graph database.

Text, Data and the Roman Roads: Semantic Enrichment

Read about semantic enrichment and the unique opportunity it offers for interconnecting objects to facilitate knowledge discovery.

4 Things NOW Lets You Do With Content

Go beyond conventional publishing with Ontotext’s News On the Web and get the feel of how you can discover and consume content with semantic technology.