TAS Tagger

Automates the tagging, categorization and analysis of text and media, enhancing content searchability across documents, emails, and articles.

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Do these questions sound familiar?

Wasting hours finding the email, document or article required instead of progression?

Pressed for time to find information for a meeting, presentation or data request?

Struggling with narrowing down the vast amount of information during search process?

If you are familiar with these issues you definitely need a tagging solution!

Welcome to the new world of NLP&ML supported document tagging

Main thoughts

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.

Success Integrated

Too many different solutions? Stuck in a selected software? Lack of effective integration?

TAS Tagger is an ultimate tool, providing the combined knowledge of text analytics packages of tech giants as:

  • Microsoft
  • Google
  • IBM
  • OpenAI

and the advanced solutions of subfield leaders as:

  • Rosette Text Analytics
  • MicroFocus
  • Neticle
  • Repustate

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:

  • search engines
  • BI tools or
  • further market-leading solutions.

The best known and most widely applied text processing methods are available:

  • topic, keyphrase and entity extraction
  • language detection
  • sentiment and emotion analysis
  • video and audio analytics

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.

Language support

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.

Work as usual, but more effective

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 Engine that combined with the knowledge of TAS Tagger puts a real Insight Engine in your hands.

Features of TAS Tagger

The values are ​​in your hands. Treat them the way you want

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).

TAS Tagger graph
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.

Other features

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.

E.g.:
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:

  • enriching its data (tags are metadata)
  • making them more easily searchable (documentations or even emails)
  • improving its data quality

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.

Other products of TAS Platform

We have also developed other software services in TAS Platform.

TAS Enterprise Search Engine 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.

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. 

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.

Technical description

  • 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
  • For development:
  • Cloud API
  • On Premise API
  • Java SDK is available

Integration with other products

  • Precognox TAS Platform
  • Microsoft Text Analytics
  • IBM Text Analytics
  • Rosette Text Analytics
  • Google Text Analytics
  • Neticle Text Analytics

Questions and Answers

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.

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