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TDM for subscribers

For subscribers Pվ��Ƶ offers a large variety of TDM tools such as metadata and fulltext APIs, to be applicable to both open access and subscribed resources. See and contact tdm@springernature.com if you have further questions.
 

TDM for non-subscribers

Non-subscribers are offered a variety of TDM tools for our Open Access resources, such as our Open Access fulltext API (see ). TDM requirements from non-subscribers for pay-walled content are treated on a case-by-case basis. Please contact tdm@springernature.com.
 

TDM for Open Access content

For Open Access content we are offering a powerful Open Access fulltext API (see ). The Open Access API provides metadata and fulltext content where available for more than 900,000 online documents from Pվ��Ƶ open access XML, including BioMed Central and SpringerOpen journals.

What about image mining

At the moment Pվ��Ƶ does not offer any API for image mining.
 

What about argumentation mining

“Argumentation mining aims to automatically detect, classify and structure argumentation in text. Therefore, argumentation mining is an important part of a complete argumentation analysis, i.e. understanding the content of serial arguments, their linguistic structure, the relationship between the preceding and following arguments, recognizing the underlying conceptual beliefs, and understanding within the comprehensive coherence of the specific topic.” (Mochales, R. & Moens, MF. Artif Intell Law (2011) 19: 1. )

Argumentation mining can be considered as a subset of text mining. If you are planning to locally store non-open-access content during an argumentation mining project, please get in contact with tdm@springernature.com to discuss options.

TDM

TDM (Text and Data Mining) is the automated process of selecting and analyzing large amounts of text or data resources for purposes such as searching, finding patterns, discovering relationships, semantic analysis and learning how content relates to ideas and needs in a way that can provide valuable information needed for studies, research, etc.

Argumentation mining

“Argumentation mining aims to automatically detect, classify and structure argumentation in text. Therefore, argumentation mining is an important part of a complete argumentation analysis, i.e. understanding the content of serial arguments, their linguistic structure, the relationship between the preceding and following arguments, recognizing the underlying conceptual beliefs, and understanding within the comprehensive coherence of the specific topic.” (Mochales, R. & Moens, MF. Artif Intell Law (2011) 19: 1. )

XML parsing

“XML parsing is the process of reading an XML document and providing an interface to the user application for accessing the document.” (Li C. (2009) XML Parsing, SAX/DOM. In: LIU L., ÖZSU M.T. (eds) Encyclopedia of Database Systems. Springer, Boston, MA. )

API

“API stands for application programming interface. An API helps expose a business service or an enterprise asset to the developers building an application. Applications can be installed and accessed from a variety of devices, such as smartphones, tablets, kiosks, gaming consoles, connected cars, and so forth. Google Maps APIs for locating a place on a map, Facebook APIs for gaming or sharing content, and the Amazon APIs for product information are some examples of APIs. Developers use these APIs to build cool and innovative apps that can provide an enriching user experience. For example, developers can use APIs from different travel companies to build an app that compares and displays each travel companies’ price for the same hotel. A user can then make an informed decision and book the hotel through the company that is providing the best offer. This saves the user from doing the comparison on his own—thus improving his overall experience. APIs thus help provide an improved user experience.” (De B. (2017) API Management. Apress, Berkeley, CA. )

API key

“An API key identifies the application using an API. It provides a simple mechanism to authenticate the apps. API keys allow an API to determine which applications are using it. API keys are generally long series of random characters typically passed as an HTTP query parameter or header. This makes it easy to use an API key in an API request for application authentication. API keys are also known by other names, such as app ID, client ID, app key, or consumer key.” (De B. (2017) API Management. Apress, Berkeley, CA. )

XML (Extensible Markup Language)

“XML is a standard for the modeling of data using a tree structure. It consists of rules defining the structure of documents that can store data consistent with the defined structure. XML therefore is a framework for the definition of data structures without describing how an actual document can be processed.” (Lupp M. (2008) Extensible Markup Language. In: Encyclopedia of GIS. Springer, Boston, MA. )

IE (Information extraction)

“Information Extraction (IE) is a task of extracting pre-specified types of facts from written texts or speech transcripts, and converting them into structured representations (e.g., databases).” (Ji H. (2009) Information Extraction. In: LIU L., ÖZSU M.T. (eds) Encyclopedia of Database Systems. Springer, Boston, MA. )

NLP (Natural Language Processing)

“Natural Language Processing (NLP) … aims at developing computational methods and algorithms for understanding and generating human languages.” (Rus V. (2013) Natural Language Processing. In: Runehov A.L.C., Oviedo L. (eds) Encyclopedia of Sciences and Religions. Springer, Dordrecht. )