Knowledge Technology Era

Software Solutions

We can extract information from your large numbers of text documents. This requires automated access to the full-text content of large numbers of articles!

Text and content mining is of central importance for internet based media services and intelligent search services. Text Mining services already are of commercial interest for the media and publishing houses, for on-line and off-line journalism, quality analysis and assurance in industries, patent and technology mining, trend mining and trend management, and media and marketing analysis.

In the Text mining context we can do:

  • Indexing documents and datasets
  • Entities identification and normalization against reference data
  • Information extraction: from semi-structured to structured
  • Semantic/lexical resource acquisition from texts
  • Sentiment analysis

We can provide these services for your Data:

  • Social media data analysis: Today, social media is one of the most prolific sources of unstructured data. Social media is increasingly being recognized as a valuable source of market and customer intelligence, and companies are using it to analyze or predict customer needs and understand the perception of their brand. In both needs text analytics can address both by analyzing large volumes of unstructured data, extracting opinions, emotions and sentiment and their relations with brands and products.
  • Risk management: No matter the industry, insufficient risk analysis is often a leading cause of failure. It can dramatically increase the ability to mitigate risk, enabling complete management of thousands of sources and petabytes of text documents, and providing the ability to link together information and be able to access the right information at the right time.
  • Knowledge management: Not being able to find important information quickly is always a challenge when managing large volumes of text documents. Organizations are challenged with a tremendous amount of information that could potentially be useful for their largest profit center: new product or service development.
  • Cybercrime prevention: The anonymous nature of the internet and the many communication features operated through it contribute to the increased risk of internet-based crimes. Today, text mining intelligence and anti-crime applications are making internet crime prevention easier for any enterprise and law enforcement or intelligence agencies.


  • Customer care service: Text mining, as well as natural language processing (NLP) are frequent applications for customer care. Today, text analytics software is frequently adopted to improve customer experience using different sources of valuable information such as surveys, trouble tickets, and customer call notes to improve the quality, effectiveness and speed in resolving problems. Text analysis is used to provide a rapid, automated response to the customer, dramatically reducing their reliance on call center operators to solve problems.
  • Fraud detection through claims investigation: Text analytics is a tremendously effective technology in any domain where the majority of information is collected as text. For example, insurance companies are taking advantage of text mining technologies by combining the results of text analysis with structured data to prevent frauds and swiftly process claims.
  • Contextual Advertising: Digital advertising is a moderately new and growing field of application for text analytics.
  • Decision Making: text mining really makes the difference, enabling the analyst to quickly jump at the answer even when analyzing petabytes of internal and open source data. Our text mining Services are able to monitor thousands of sources and analyze large data volumes to extract from them only the relevant content.
  • Content enrichment: While it is true that working with text content still requires a bit of human effort, text analytics techniques make a significant difference when it comes to being able to more effectively manage large volumes of information. Text mining techniques enrich content, providing a scalable layer to tag, organize and summarize the available content that makes it suitable for a variety of purposes.

Spam filtering: spam is a major issue for internet service providers, increasing their costs for service management and hardware\software updating; for users, spam is an entry point for viruses and impacts productivity. Text mining techniques can be implemented to improve the effectiveness of statistical-based filtering methods.