CO-OCCURRENCE EXTRACTOR

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1 Page 1 of 7 CO-OCCURRENCE EXTRACTOR Sede opertiva: Piazza Vermicelli Rende (CS), Italy

2 Page 2 of 7 TABLE OF CONTENTS 1 APP DOCUMENTATION HOW IT WORKS Input data Output data Basic workflow example 6 2 API DOCUMENTATION... 7

3 Page 3 of 7 1 APP DOCUMENTATION 1.1 HOW IT WORKS Co-Occurrence Extractor APP is a normalization task that allows to extract keywords and find cooccurrence between keywords from a corpus of documents; this feature aims to help user to easily understand main topics of the entire corpus of documents, but, in addition to the typical results of the Topic Extractor APP, user can have more information about which keyword is most frequently associated with another keyword in the entire corpus. It uses natural language processing techniques used in Topic Extractor APP and applies statistical techniques to obtain co-occurrence analysis.

4 Page 4 of INPUT DATA This APP allows to extract keywords and find co-occurrence between keywords from a corpus of documents; this feature aims to help user to easily understand main topics of the entire corpus of documents, but, in addition to the typical results of the Topic Extractor APP, user can have more information about which keyword is most frequently associated with another keyword in the entire corpus. It uses natural language processing techniques used in Topic Extractor APP and applies statistical techniques to obtain co-occurrence analysis. Input data shows in the following Figure 1 return all keywords co-occurrence detected in the corpus of documents given by the Descrizione_Completa_Idea field by processing the Italian natural language; this field is given in output from the previous app in the workflow,. Descrizione_Completa_Idea field, in the next example, contains descriptions of some customers' ideas about a contest for a specific product. Figure 1 input data. 1.3 OUTPUT DATA This APP gives back, for each extracted entity, a set of three elements: 1. cooccurrence: number of occurrences of specified pair of keywords in the input corpus; If this keyword pair was detected in 2 of 10 documents, then the co-occurrence value will be equal to 2; 2. keyword1: the first keyword of the pair; 3. keyword2: the second keyword of the pair. This set of elements can be returned in an excel spreadsheet or a data cube whose metadata depending on data extracted and returned in output. You can see, in the following figures, an example of output data (Figure 3) based on the input data given (Figure 2): Figure 2 - example of input text (an excel sheet previously processed and prepared)

5 Page 5 of 7 Figure 3 - example of output data Figure 4 - example of excel sheet output data This example is a sample of output where Co-Occurrence Extractor APP extracts from a columns of an excel sheet all keyword s pair co-occurrence between text contained in that columns. The excel format output

Page 6 of 7 allows users to sort co-occurrences in descending order, facilitating the identification of pairs of most relevant keywords within the corpus of documents. 1.

6 Page 6 of 7 allows users to sort co-occurrences in descending order, facilitating the identification of pairs of most relevant keywords within the corpus of documents. 1.4 BASIC WORKFLOW EXAMPLE Co-Occurrence Extractor APP needs some extraction app before in the workflow that can get some text to process, so you can create a simple flow as shown in the following Figure 5. You can set input parameter and watch the results by the watcher button as shown in the following Figure 6. Figure 5 - simple Co-Occurrence extractor workflow example Figure 6 - the watcher panel.

7 Page 7 of 7 2 API DOCUMENTATION For information about how to use Co-Occurrence Extractor API in your application, send us a message to info@altiliagroup.com.

NORMALIZED SENTIMENT ANALYZER

Page 1 of 6 NORMALIZED SENTIMENT ANALYZER Sede opertiva: Piazza Vermicelli 87036 Rende (CS), Italy Page 2 of 6 TABLE OF CONTENTS 1 APP DOCUMENTATION... 3 1.1 HOW IT WORKS 3 1.2 Input data 4 1.3 Output