NelSenso.Net: Text Mining Apps

NelSenso.Net is a collection of text-mining apps very useful for reading, writing and studying more quickly through artificial intelligence algorithms and "text mining", that is the set of techniques that allow the automatic extraction of information starting from a corpus of textual documents or web pages (hypertext). At an elementary level, these tools help to quickly obtain an overview of the content of a text or set of texts, or to extract the main keywords (keywords) and most salient phrases (keyphrases).
NelSenso.Net tools are based on the principle of semantic reinforcement between salient phrases and keywords: a sentence is all the more important the more relevant words are present in it, and moreover, a word is all the more "key" in the more relevant phrases it is organically present. The topics or themes of the elaborated text are extracted with artificial intelligence and machine learning algorithms (K-means text clustering). Languages supported: Italian, English, French, German, Spanish, Portuguese, Russian, Polish, Swedish, Czech, Roumanian, Bulgarian, Hungarian, Arabic, Persian, Bengali, Hindi, Marathi.

NelSenso.Net apps are aimed at students, teachers, copywriters, journalists, editors, editors, SEO & SEM Specialists, web marketing operators in general.




Summazer

Summazer Icon Summazer is the free app capable of "squeezing" a text or a web page and extracting its juice, that is the sentences with the highest information content, to generate an automatic online summary of the processed text. Therefore to summarize a text, enter the text or the address of the page to be summarized, select the language (in addition to Italian it supports texts and sites in: English, German, Spanish and many other languages) and the desired summary percentage. After the possible spelling check, the most important sentences are highlighted where the size of the characters is proportional to their relevance.
The Summazer report also shows: the graph of the semantic relevance trend, an indicator (QoT) of the quality of the processed text and the main hashtags that can be deduced from the text.
If the quality (QoT) is low it may depend on the presence of spelling errors, an excessive use of obsolete / foreign words or the processed text is full of sentences that are not very related to each other from a semantic point of view (as happens, for example, for example, if you summarize an entire web page instead of selecting only the text that actually conveys the meaning of the article).

Summazer

Abstrazer

Abstrazer Icon Abstrazer is the free app that can generate an automatic abstract of an article or web page. To write the abstract of an article or a thesis, just enter the text of the article or the address of the web page in which it is published and select the language (in addition to Italian it supports texts and sites in: English, German, Spanish and many other languages). You will immediately get an extract of the text elaborated with the most semantically relevant phrases.

Abstrazer



IRezer

IRezer Icon IRezer the web application that allows the automatic extraction of keywords (tags) and the most salient sentences of a text or web page. To extract keywords and keyphrases from a text/hipertext, therefore, enter the text or the page URL, select the language (supports texts and websites in: Italian, English, German, Spanish and many other languages) and the desired granularity. You will immediately get the tables of keywords and the most important phrases with its saliency score. It can order the results by saliency score or reading order.

IRezer

Clustezer

Clustezer Icon Clustezer is the app that allows the automatic extraction of the main topics of a text or web page through the automatic classification of the keyphrases contained in the text. To obtain the summary of topics, enter the text or the address of the page to be processed, select the language (supports texts and websites in: Italian, English, German, Spanish and many other languages) and the number of expected topics (clusters). You will get the summary of the topics with the relative sets of related phrases found in the processed text.


Clustezer