What is SBSGRID ? Our engine kickstarts contextual reasoning: Learn more
Frequently Asked Questions
What is Contextual Reasoning (SearchQuery) ? A SearchQuery "understands" the keywords entered which formulate the question.
It matches them to distinctive subjects / categories / concepts as well as time- and geo-/location-
information. It then returns contextual results based on multiple keywords entered which form
"human like questions" (the Linked-Data approach is used
to derive the intelligent context). These contextual connections are precise and associative (which
is unique -> contextual reasoning in a search experience). It is not a statistical or NLP (natural language processing)
approach. Technically speaking it is a superset of SPARQL functionality.
A classic semantic search matches strings with concepts but has no contextual, semantic understanding on
the data level (only on the concept level).
What is significant about this ? The user is given a tool to precisely and associatively get to information which he is
looking for. In other words: he easily discovers and finds information without knowing how to search (without
knowing the keywords). On top of that the knowledge base is intelligent which allows smart agents to conduct
See Digital Inference
What is Information Linking ? Information Linking integrates data from any datasource and structure in a virtual manner. This means that physically the
data are still separate. They appear to be combined and intelligent context is created during runtime. It is the intelligent, semantic
context that creates new business opportunities and ROI. Further more this approach eliminates many of the bitfalls in classic data
integration approaches and is the key in moving forward.
What is the difference to Semantic Search Solutions ? Semantic Search solutions add an ontology on top of a classic search (full text search). This means they
improve the ranking and show associative search results based on the ontology. However they do not work with
Linked-Data where the intelligence can be derived from the
relationships and context within the data itself.
What is Digital Inference / Digital Reasoning ? Digital inference is a distinctive operation and means to derive new facts from given facts (in other words create new
information from given one). Digital inference allows queries to be precise, associative, unambiguous and contextual.
In semantic systems this operates on linked-data or knowledge graphs which means
that more complex conclusions can be automatically conducted (machine learning, artificial intelligence).
E.g. see http://en.wikipedia.org/wiki/Inference
What is an Ontology ? In computer science and information science, an ontology is a formal representation of knowledge as a set of concepts,
terms, categories within a domain, and the relationships between them.
Ontologies are under heavy development since they will be the backbone of the future web ("web 3.0").
In the social networking domain Facebook manages the biggest ontology, linked-dataset or "social graph"
(people and their connections). See http://en.wikipedia.org/wiki/Ontology_(information_science)
What is a Dynamic Schema / Dynamic Ontology ? In classic semantic systems a data schema or ontology must be created first before data can be populated and the application
can be developed. This is very much like in the classical database world (tables and indices must be created above all).
This prevents short implementation cycles and leads to the known problem that the requirements have changed when the application is finally
ready for usage.
A dynamic ontology needs no static schema. Information is fed into the system at any given point in time and the contextual factbase
adapts automatically. Instant access through contextual searches is always active.
What are Linked-Data ?
Linked-Data is a world wide movement & technology for 'semantics' in IT systems. It brings intelligence and context into software.
The user or software agent is able to ask complex contextual questions without having to know how to ask and without having
to know where the information resides (databases, documents or websites).
In linked-datasets the data form a network of information. Whereas in a database
all semantics (categories, related subcategories, terms, concepts and relationships) are implicit and not accessible
they become explicit and accessible in Linked-Data. This allows for machine learning, digital reasoning,
semantic query, virtual information integration and smart operations on the level of information.
Linked-Data can be used behind the firewall and for cross firewall queries.
What are Semantic Agents ? A semantic agent implements the knowledge of an expert to conduct his reasoning methods. It is a small granular piece of software
that acts for a user or on behalf of other agents (artificial collective intelligence). Agents are event based and
invoke themselves whenever necessary. This requires a communication and coordination framework. The result are lean and powerful
application design patterns. Semantic agents operate on Linked-Data, Data Graphs and Semantic
Data Models. See http://en.wikipedia.org/wiki/Software_agent
What is a FTS-Server ? FTS stands for "Full Text Server" (short "Index Server"). It is an application which manages an index over free text (typically
text-files or html-files). It collects, parses, and stores data to facilitate fast and accurate information retrieval. The index enables
the quick search for a sequence of characters over a big body of text-data.
E.g. see http://en.wikipedia.org/wiki/Index_(search_engine)
SBSGRID injects intelligence into your software. The system learns
from all information added by putting it into an overall information
context. Through a "SearchQuery" the user (or software agent) instantly finds what he is
looking for. IT budgets are turned into sustainable investments because
the static information model approach is eliminated. Productivity
and intelligence in the system and between systems are brought
to the next level.
SBS Semantic Business Solutions, Inc. (c) 2007-2012