Exploiting the power of corporate data assets is the foundation of a successful business decision
Whatever means the value for the company in the enterprise data, it is essential to be retrieved and tagged properly, regardless where these values are hidden: in business documents (contracts, notes), texts available on the Internet (articles and other documents), scientific contents (essays, dissertations, published research), or even e-mails.
What is TAS Tagger?
TAS Tagger is a text analytics solution that can extract and define key terms and topics as values from textual content. These terms and named entities (eg, personal names, places, organizations, dates) are identified by computer linguistic and machine learning methods and tools. The applied combination of available methods and tools depends on the needs of the client.
Why is TAS Tagger useful?
TAS Tagger provides various advantages. Tagging bigger text bodies is improving the usage efficiency of the documents:
- enriching its data (tags are metadata)
- making them more easily searchable (documentations or even emails)
- improving its data quality
In addition, the TAS Tagger solution can provide data for automatic (machine learning based) classification of texts.
Utilizing TAS Tagger does not mean that the company has to give up the systems used so far, it only helps these applications to operate more efficiently, thus elevating the process of gaining insights to a higher level.
However, if the complex user needs necessitate also the implementation of a new search engine within the enterprise IT environment, TAS Enterprise Search is an excellent solution. The parallel application of both solutions puts a real Insight Engine in your hands.
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:
- Basis Rosette Text Analytics
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. All of these methods operate regardless of the given sector and professional field. Thus the circle of users may also be wide:
- data scientists
- HR, sales or marketing experts.
The tagging process
- definition of the text body to be tagged
- specification of tags
- controlling of how precise the tags are
TAS Tagger analyses the text body and define tags automatically or the set of possible tags can be defined by the customer in advance. In these cases we build a professional tag-database in partnership with the user. This database contains the pre-defined tags. The machine learning model uses this database and could be re-trained every time the tag-database changes. This re-training method can be accomplished by the user through the TAS user interface. The tagging process is also trackable on the same GUI. Once a tag is accepted, the software stores it. The system also stores the previously tagged text contents.
The more connections and relations are defined, the more specific tagging results are going to be available. Therefore, it is always important to build the tag database carefully.
TAS Tagger UI
TAS Tagger GUI can be created within the confines of TAS Platform (TAS Cloud service) or On Premise (locally installed). The appearance of 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.