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Text Analytics

Text Analytics is a balanced combination of process and technology, a device through which texts are sourced from different points for varying purposes. Also referred to as text mining, it precisely examines the texts coded in natural language through transposition of phrasal structures, individual words and syntaxes. Texts are collected from unstructured data sources and transformed into their numerical values in order to develop a connection with structured data. The databases, after assemblage are then scrutinized for analysis through another relevant process called data mining.

Loginworks Softwares irons out the complexities of the process through exceptional skills of its technicians coupled with the top-notch technology it integrates in its work system to deliver high quality results.
Both text analytics and text mining are borderline names for a spectrum of techniques shaped from parent technologies for the same end of processing and examination of raw unstructured and semi-structured data. However, talking about what positions these two techniques on either side of a thin line is their common prescript of converting texts into numeric. Once the pass-over is accomplished, the entire data structure can be subjected to algorithms, all at one.

It goes with common perception that techniques and technologies go hand in hand, and that said, it is implied that an insightful understanding of the text translations and application of analytical algorithm should be had to inmix both.



Text Analytics: The Practical Side of It

Till date, seven areas have been officially identified as practicable for text analytics. Each area is singularly unique, but when viewed broadly have a correlation with one another. To make this a unit clearer, one project of text mining requires techniques to be streamed from multiple of these seven areas of precise accomplishment. The practicable areas have been inductively spotted and named here in:


  • Search and IR: Storage of text documents following by its frequent retrieval as through search engines. This process encompasses the keyword search process of search engines.
  • Information Extraction: This is detection and derivation of information by their relevance meter from unstructured databases with the aim to format them into structured data, or at least semi-structured forms.
  • Document Classification: Documents derived from related sources are grouped in snippets, passages or in whole documents. The classification is done following examples set by certain models.
  • Document Clustering: Data mining cluster methodologies are put to use in order to categorize documents as necessary in their assigned slots.
  • Data Mining: Also referred to as web mining, it is extraction of data from the Internet, with focus adjusted on coherence and scale of the Internet.
  • Natural Language Processing: Processing of low-level computational language and making out the commands and tasks.
  • Concept Extraction: Categorizing of singular words and collective phrases into semantically identical clusters.

Loginworks explores all these areas with the plethora of projects it receives, and with that, it has hands-on experience in all these fields.

Big Data and Text Analytics: One That Leads to Another

There is a distinct connection between big data and text analysis. They are the what and why of data that is created and processed every day. Text analytics refer to pre-processing of data. It is the method of finding additional structure in the visibly and technically unstructured texts. Text analysis serves to predict behavioral patterns, thus adding another dimension to individual documents. The process involves finding out of new variables that are associated with social media and predictive analysis. On a greater dimension, it analyzes 90% of text sourced from the Internet, and 50% social media analysis. Making it simple and digestible, text analysis is a way of enriching the semantic quotient of data by adding new inputs into it. Loginworks understands the importance of keeping both the subjects overlapping in the context of text analysis to grind out maximum and undisputable results.

Dissecting the Process Anatomy into Multiple Sub-Processes

The broader effort of text-analysis can be split up into multiple sub-tasks, much of which has been briefly explained in the following bullets.


  • The first task of text analysis is extraction of information through proper identification of corpuses. Whether it’s a CMS, computer database, file system or the Internet, collection through identification is preponderant.
  • There are two types of text analysis techniques, namely, natural language processing as discussed above and implementation of advanced statistical methods. The former takes linguistic analysis, while the later is core technical.
  • The third task is identification of named text features that could be individuals, name of places, organizations, stock ticker symbols, and much more. Disambiguation is another part of this where contextual clues are identified to establish the correlation.
  • Next, the process deals with pattern indentified text features, which mostly range from telephone numbers to mail credentials. Pattern match technique is used to make the identifications in this case.
  • Grammar does play a role in this, and such is the purpose of co-reference. It finds out the noun phrases, and along with that other terms that have referential link with the subject.
  • Extraction process of text analytics is not blunt. It recognizes the association, which in other words can be termed interrelation, before extraction..
  • When it comes to analysis of a certain social media database, it takes to analyze the sentiments of data, and by sentiment, it could be any value, such as moods, emotions, bias, opinions, etc.
  • Lastly, the analysis takes into account qualitative quotient of the system. This takes making distinction between a human judge and a bot, in their effort to establish grammatical or semantic values of the same. This is mostly done when the project involves psychological profiling.

Loginworks is one of those leading concerns in this arena with a rare profile to offer complete array of services through its ever-active team of technologists and most superior technologies used to turn out the projects with maximum infallibility.

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  • - Project relationship
  • - One time delivery
  • - Price: Starts from $150
  • - Clean and correct data
  • - Project relationship
  • - One time delivery
  • - Price: Starts from $150
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