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KDnuggets Home » News » 2016 » May » Software » Data Science and Cognitive Computing with HPE Haven OnDemand: The Simple Path to Reason and Insight ( 16:n17 )

Data Science and Cognitive Computing with HPE Haven OnDemand: The Simple Path to Reason and Insight


HPE Haven OnDemand is a diverse collection of APIs for interacting with data designed with flexibility in mind, allowing developers to quickly perform data tasks in the cloud. See why it is a simple path to reason and insight for data science and cognitive computing.



Graph Analysis

Graph analysis is recognized as an incredibly useful tool for understanding large volumes of highly-connected data, with all sorts of applications in data science and cognitive computing. The Haven OnDemand Graph Analysis APIs provide various methods to interrogate a knowledge graph structure. In their current form, the graph APIs can be used with a graph structure derived from Wikipedia’s link architecture.

Current supported tasks include finding the common neighbors of specified nodes (Get Neighbors API), attaining the shortest path between 2 nodes (Get Shortest Path API), and suggesting nodes that a specified is close to, but does not connect to (Suggest Links API), among others.

Prediction

Prediction is one of the most common and useful contemporary data-related tasks, used to classify, predict, and analyze data. Haven OnDemand provides 3 Prediction APIs: the Predict API, The Train Prediction API, and the Recommend API. Prediction was covered extensively in a previous article.

Text Analysis

Text is ubiquitous, and its analysis has numerous use cases in both data science and cognitive computing. The Text Analysis APIs are useful for providing additional information about text, of which Haven OnDemand offers many.

For instance, the Language Detection API returns the language that a provided piece of text is written in. The Document Categorization API allows for the categorization of documents, according to an operator-defined set of categories. Key concepts can be extracted from text using statistical methods via the the Concept Extraction API; returned best terms and phrases can be used as document summaries or treated as key phrase highlights.

The Entity Extraction API is very interesting: its goal is to find snippets of information (words, phrases, or other specific pieces of data) from a body of provided text. The API is able to extract the names of people, places, or companies, phone and credit card numbers, and more. What’s more, the API returns valuable metadata, such as Wikipedia links and stock ticker symbols, about the found entities.

Text Analysis

One of the most common text analytics insight tasks is sentiment analysis. Haven OnDemand’s Sentiment Analysis API is able to perform said analysis on supplied text and return whether the sentiment is positive, negative or neutral. The Sentiment Analysis API is built with both a dictionary and defined patterns for accurately extracting the sentiment that can be useful for determining how customers and others feel about topics being discussed. Unlike other APIs that only return the aggregate score for the entire text, Haven OnDemand also returns the sentiment for individual topics within the text, thereby providing more contextual and in-line insights.

Sentiment analysis

Conclusions

HPE Haven OnDemand is rife with flexible and powerful interaction with structured and unstructured data, from audio to text to graphs and beyond. They can be employed alone or in combination for extracting insight and performing reasoning. And it’s all available from one platform!

Not exciting enough? As extensive as the Haven OnDemand APIs are, they simply cannot be expected to do everything. But with some ingenuity and creativity, there’s no reason that Haven OnDemand can’t do the heavy lifting and make common third-party APIs even more useful. With the flexibility of Haven OnDemand’s APIs, a developer could transcribe audio to text, determine its language of origin, and then use this information to call an external language translation API. The results of this third-party service could then be processed further by Haven OnDemand, for instance by performing classification, categorization, sentiment analysis, text tokenization, and more. These are powerful tools for limitless innovation.

HPE Haven OnDemand offers a wide range of APIs for use in data science and cognitive computing. Extracting reason and insight from your data could not be any more simple or straightforward, and the power and flexibility of Haven OnDemand is attracting the attention of thousands of developers, researchers, and practitioners.

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Note: the article was commissioned by HPE, but written by an independent KDnuggets expert.


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