Matheo Analyzer

Matheo Software > Products > Matheo Analyzer

Matheo Analyser

Database Analysis and Information Mapping.

Matheo Analyzer is a flexible and an easy-to-use software which permits to explore efficiently important volumes of data and converting them into strategic information.

General Points

Matheo Analyzer is a decision making software which permits to get a dashboard, information maps, syntheses and indicators generated from large sets of information.

Usually, it is used by experts and analysts on patents and scientific papers to make maps on main players and technologies, detect trends, assure a scientific, strategic, commercial and competitiveness monitoring.

Matheo Analyzer works from a set of structured information which come from large specialized bases (free such as some patent databases or PubMed, or commercial through providers such like Questel-Orbit, Dialog, STN, ...) or from company homemade databases.

Analyzes realized by Matheo Analyzer bring key elements in activities such as :

Competitor technology positioning
Innovation and investment policies
Research evaluation
Technologic trends
Patent portfolio analysis
R&D and research team detection
Technology, Patent and Competitiveness Monitoring

It is a necessary tool for professionals working in field which information production to analyze is important and want to benefit from a clear and reliable knowledge of these information.

Information Security

Storing

With Matheo Analyzer, your data are stored on your PC, they are not on the Internet browser on which you can't control the security.

Confidentiality

Your research (questions and results) never transit by an extern provider. You keep the command of your information.

Matheo Software never accesses to its clients data and requests

Functionalities

Information Importation

Importation assistant

Matheo Analyzer permits every structured files importation (bibliographic format, CSV files, …) which come from public or private databases (Esp@cenet, PubMed, Questel-Orbit, Dialog, STN, …) thanks to a simple and performing assistant which offers defines the type of files and fields to be imported.

Possibilities to use importation pre-established rules

Concerning files importation from only one data source, Matheo Analyzer proposes you to use importation pre-established rules which permit you to simplify the step of data importation.

(More information >)

Information fine extraction

With Matheo Analyzer you can easily extract particularly relevant information, from a multi-criteria or multi-information field.

Example: selection of the country in field dedicated to the address.

Patents Importation from Esp@ceNet via Matheo Patent

Matheo Analyzer permits simple and fast importation of all exportation files from Matheo Patent software.

Data Preparation

Subset data creation

Matheo Analyzer permits creation of subsets thanks to information selection tools in order to realize accurate analyses on subset data.

Example: Subset per Country, City, Technology, …

Automatic cleaning and imported data correction

Matheo Analyzer permits to standardize data thanks to the use of correspondence tables and data search, selection and modification tools

Concept extraction

Matheo Analyzer offers tools which permit free word processing (titles, summaries, …) via automatic extraction of concepts and keywords present in the data.

Graphic representations, information mapping

Maps, analyses and indicators are based on graphic representations sets which permit synthesis, visual analyses and information mapping. Those graphic representations create high added-value information on which company decisions will be inspired on.

Matheo Analyzer offers three types of graphic representations :

Histograms (horizontal, vertical, pie charts)
Double-entry matrix
Relationship networks

Those representations fit one or several criteria in the same time such as technologies, dates, companies, authors, ...

This is possible to integrate an extra parameter in the representation via the insertion of blocking elements (a technology, a company, ...)

Clustering

Matheo Analyzer offers several automatic clustering methods in order to be able to create information subsets quickly and easily.

Clustering permits to get quickly a dynamic classification of data important volumes.

Matheo Analyzer permits the easy and rapid creation of clusters by selection of only few parameters. You only have to choose the field to use as reference and select the definitive number of clusters to create.

Matheo Analyzer also permits subset creation for clusters integrating an important volume of data.

Matheo Analyzer offers different methods of clustering :

K-Means++
By propagation
By dendrogram

News 4.0

Data Importation

New importation method: "Academic Extraction"

Mainly intended for fields Addresses and Affiliations, it used to extract portions of very specific chain in order to rebuild a "normalized" form.

Its own sequence can be produced according to several criteria: University, Faculty, Institute, Hospital, Centre, Laboratory, Department, Email, Country.

Exemple: "CRRM, univ. Aix-Marseille III, Av. Escadrille Normandie, Marseille, France;" form

will produce "Univ. Aix-Marseille III, France"

by selecting University and Country criteria

Improvement of the importation rules
Improvement of the CSV files importation
- Management of the first line whether it contains the field names
- Management of the fields with "Text Qualifier"

Adding parameters:
- Kind of files (Patent, Medical, Scientific, Others)
- Kind of fields (several types are available depending on the type of source file)
Adding "Notices" button in the Step 5 of the importation wizard
Extraction Lexical: Stemming - 16 additional languages

MyAnalyzer

The identification of selected fields during the importation phase allows Matheo Analyzer to provide automatically relevant analysis in tables, graphs or matrix.

Additional Widgets, such as an internal Full-Text search engine, a Medline Web-Service, Esp@cenet or Google, are also available for an intuitive navigation in the imported corpus, for patent searches, medical notices, ...

Clustering

K-Means

Entry: Simplification of the parameters
- Original field enabling the clusterisation
- Maximal number of classes to create
- Number of clusterisation (Repetitions)
Output:
- Quality index for clustering
- Naming classes with most relevant terms
- Quality index for each class
- Singularity index of the class
- Index grouping class (Compact or not)
- Display of the main terms of the class with their percentage of use
To come: Navigation clustering using a graph

HAC - Hierarchical Agglomerative Clustering (Dendrogram)

In the hierarchical cluster analysis, "Dendrogram" graphics are used to visualize the way clusters are formed.

The user can choose graphically the number of classes that will compose the clustering.

Entry:
- Original field enabling the clusterisation
Output:
- Classes composing the clusterisation

Propagation

Based on the principle of chaining, this type of clusterisation is very useful to find combinations of authors.

Entry:
- Original field enabling the clusterisation
Output:
- Classes composing the clusterisation

Other improvements

Backup files creation before and after opening project
Possibility to clear an "Original" field
Display information about the field
Fields creation by Percentile method
Visualization of notices: Layout + highlight imported fields
Visualization in real time of the number of forms from the Local Search Engine
Improved display of different graphs and matrix
Matrix:
- Displaying the arithmetic sum of the values in cells
- Adjustment of the size of rows and columns
Chart:
- Possibility to save graphical design template
- Possibility to archive graphs
- Export to Txt
- Export to Excel
To come: New graphical component for network representation

My Analyzer