Huge corporate data assets are repositories of essential values for making appropriate business decisions. To exploit them properly, all the details that are really important must be recognized. No one is curious about conjunctions. TAS Tagger finds components that are useful for getting insights. Names, locations, emotions, currencies, amounts or even license plates? The list is almost endless. Our solution extracts all values so that the company data mass is not wasted.
What is your value out of it? Feel free to decide.
Company data causes a lot of headaches. Their transparency is impeded by a number of obstacles: the different format and structure, the variety of repositories and the lack of appropriate software solutions or integrations to other systems within the company.
In addition to the issues above, we also have to reckon with the challenge caused by the constant expansion of data, especially available information generated outside the corporate environment.
In order to make well-founded business decisions, it has become necessary to process the entire available text content of the company’s internal and external data. Taking into account the significant amount of data, manual processing is out of the question. Insights can only be extracted automatically from these, using NLP (Natural Language Processing) and ML (Machine Learning) methods and tools, because it is impossible to read everything manually before a decision is made.
TAS Tagger is an ultimate tool, providing the combined knowledge of text analytics packages of tech giants as:
and the advanced solutions of subfield leaders as:
Would you like to learn more about TAS Tagger or additional solutions of TAS Platform? Write us or send a message using the contact form at the bottom of this page.
In addition to the insights gained the required information can be processed immediately with additional systems applied by the different experts of divisions.
These applications may be:
The best known and most widely applied text processing methods are available: topic, keyphrase and entity extraction, language detection, sentiment and emotion analysis. All of these methods operate regardless of the given sector and professional field. Thus the circle of users may also be wide:
Learn more about how TAS Tagger helps in article categorization.
Relying on insights extracted solely from the company’s internal data in business decisions is outdated. According to a research 92 percent of data analytics professionals said their firms needed to increase use of external data sources.
Collect and connect the relevant web content provided by our TAS Data Collector solution. Mark what you need from the World Wide Web, we deliver it(daily). In addition,
with a combination of TAS Data Collector and TAS Tagger, you get instant access to values worldwide.
The availability of important information in company data is the key to step onto the path leading to real insights. Today, an average business user only reaches 20% of the essentially required company data. Do you think an 80% blindspot can lead to an accurate business decision?
Or you’d rather be one of those who aren’t wandering blind amongst business data?
The effective tagging procedure supports the insight-driven business decision making by retrieving and delivering the required data.
Reach your data more precisely by TAS Tagger.
TAS Tagger opens up new perspectives also for the internal or external Data Science team.
In addition to using automatic tags, they may build supervised Machine Learning (ML) models, that can also be connected.
The manual tagging function (annotation) can be used to prepare documents for building models. The implementation of these models can support the automatic categorization of text contents for all user within the company.
We know well that every business face different challenges. In case of domain specific tagging requirements we can lend your data experts a helping hand.
The range of the available languages for the integrated services is also wide. The table below shows the language availability. Additional languages are also possible to choose for some services, including 26 European languages. Please inquire about these by the contact form at the bottom of the page.
One of the biggest advantages of TAS Tagger that it is not necessary to give up the systems used so far within the company, it only helps these applications to operate more efficiently, thus elevating the process of gaining insights to a higher level.
Since search engines are the most common way to take advantage of the benefits provided by the tags, we have developed our own search solution, TAS Enterprise Search that combined with the knowledge of TAS Tagger puts a real Insight Engine in your hands.
TAS Tagger automatically extracts the pre-defined values from text bodies, the next steps – the usage of the functions to get real insights – depends on the user.
Let’s see how it works and what kind of special features are available:
The extracted terms can be formed into a single set of knowledge base in the TAS Tagger interface, linking them together and then always using the related terms together (broader and narrower terms, synonyms, co-occurences).
In addition to the above, a dedicated function is available allowing the user to compile a stoplist that contains the eliminated terms.
An unlimited number of parallel models can be built with the listed features, tailored to the needs of a given user or group.
All newly created documents in the company’s data assets can be automatically tagged through this common knowledge base and become available for further enterprise software solutions
(for example, tags can operate as filters in the enterprise search engine).
This way, you can always make a business decision based on insights gained from the latest information.
Tags provided by TAS Tagger API can be utilized by any enterprise software regardless the type of the attached application: search engine, BI tool or other analytical solution.
Thus, all gained values can be utilized by every departments, divisions or particular team of the company parallelly and unlimitedly.
The solution can be a great leap forward in the everyday work of all departments. Cooperation between the marketing and sales department can become closer, the HR department can be more efficient, managers can get a more accurate picture of internal processes, but even a new dimension can be opened for the data science team in the field of data processing.
The tags provided by TAS Tagger can also operate as defined filters in the applied enterprise search solution. By these extreme filtering capabilities your job will be done faster and much more effective. Imagine, the required information is just a click away without typing a word.
Manual tagging: For model building purposes as mentioned above, or if the tag you are looking for is not added with automated tagging.
Primary tag: Set your primary tag in synonym or co-occurence relations. So even if the content contains a word connected with the primary tag, you get the primary tag suggestion too.
The following relation is added to the Tagger: Colonel Sanders is in co-occurence with KFC.
If you tag this text: KFC is offering free delivery next week
You get Colonel Sanders as a tag suggestion.
TAS Tagger provides various advantages. Tagging bigger text bodies is improving the usage efficiency of such documents:
That’s how TAS Tagger helps in exploiting the values in your company data. Turn these values into relevant insights by your current system tools or by TAS Enterprise Search leading you to the proper business decision.
Screenshots from Tagger GUI
The Tagger GUI can be created within the confines of TAS Platform (TAS Cloud service) or On Premise (locally installed). The appearance of TAS Tagger is consistent with the corporate identity of TAS Platform. The visualization and the other parts of the user interface are also configurable. The particular solution depends on the customer’s needs.
Screenshot GIFs from Tagger GUI
We have also developed other software services in TAS Platform.
TAS Enterprise Search is an Elastic based enterprise search engine with massive data searching capability (access rights to your data) that enables the user to accomplish searches in the data collected by TAS Data Collector. It is a perfect combination when you not just need the data, but you want your dataset to be effectively searchable. TAS Enterprise Search is also capable of finding named entities (ie. like company names or date) in various formats. The existence of TAS Enterprise Search is the basis of using TAS Search Log Analyzer, because it can only visualize searching results launched in TAS Enterprise Search. Find out more by reading the TAS Enterprise Search use case.
TAS Enterprise Bulk Search is a supplementary service for TAS Enterprise Search dedicated to simplify and shorten the complex and time-consuming search processes which previously could only be done one by one.
TAS Alarmlist is a text analytics solution for automatizing the time-consuming repetitive queries in the enterprise environment. The service sends notifications in several ways if it finds matches between company data assets and search terms contained in the compiled watchlist.
TAS Thesaurus Manager is a thesaurus-building module that facilitates the more optimal and sophisticated operation of the TAS Enterprise Search engine. Find out more by reading the TAS Thesaurus Manager use case.
TAS Search Log Analyzer is an analyzing tool that provides the user information about your search log and search history. It gives the user actionable insight with special emphasis of search expressions, their frequency and efficiency.
TAS Data Collector is able to collect web-based data content in a structured format so as to make this content available for information systems or for further processing and analysis. Find out more by reading the TAS Data Collector use case.
Initial resource requirements (On Premise)
x86_64 CPU at least 4 core
at least 16GB RAM
35GB disk (it may grow as the amount of logs increase)
64-bit Linux, Windows, or macOS – 64-bit JDK 1.8 or above
Availability and platform support
On Premise API
Java SDK is available
Precognox TAS Platform
Microsoft Text Analytics
IBM Text Analytics
Basis Rosette Text Analytics
Google Text Analytics
Neticle Text Analytics
What is the duration of implementing a TAS Tagger solution? – Every TAS tagging project has different requirements, it could be realized even in 15-30 days. A Machine Learning-based tagging solution needs more time, especially if you don’t have annotated data yet.
Can you handle special requirements? – Sure, no problem. We are not only the owners of TAS Platform solutions – but also a software development enterprise so we are capable to develop your custom solution.
Are you prepared to get into business with enterprises outside of Hungary? – We have several partners in Europe and we also have overseas customers. We all do speak in English, and some of us in German.
Do you have other questions about the product or the quotation? Send your message.