Top 5 Text Mining Features of New Age Enterprise Search Software

Today when Big Data is a concept that is increasingly gaining importance with the continuous growth of enterprise data, what enterprises need is a powerful enterprise search tool. The reason is that the data collected by enterprises is mostly unstructured and this data cannot be analyzed using the traditional keyword based method. The keyword based method works best when the data is organized in a systematic manner and optimized with keywords. However, the data that enterprises collect today is from an array of different sources and is present in multiple formats – emails, social media feed, images, documents, to name a few.

The new age enterprise search software is designed to help businesses make the best use of the large volumes of enterprise data, because they have powerful in-built text mining capabilities that make them capable enough to analyze the most complex unstructured data. 3RDi Search is an example of a new age enterprise search software that comes with every text mining feature that enterprises would need. Another example of a similar software is Swiftype that is also equipped with key technology to successfully analyze complex unstructured data. This article looks into the key technologies that power the new age enterprise search software.

1] Natural Language Processing (NLP)

Natural Language Processing or NLP is a technology that enables computers to understand, process, and analyze human language. It is technology that is based on artificial intelligence (AI) and its objective is to simplify the interactions between computers and humans. It enables enterprise search software to understand and process user queries more effectively and fetch the results that are useful to the user.

2] Semantic Technology

Semantic technology is nothing but the search technology that focuses on the meaning of the query in order to fetch the most relevant results. This is in contrast with the traditional keyword-based approach whereby the search engine only takes keyword matches into consideration when finding results for a query. Semantics has proven to be a breakthrough in increasing the relevancy of enterprise search, boosting user experience by large volumes.

3] Search Analytics

Enterprise search witnesses thousands or even lakhs of queries every day which results in large volumes of data. This data or search logs are not used by enterprises for any purpose because they don’t have any tool to do so. However, enterprise search software today offer search analytics capability to help Enterprises derive useful insights from this data that talk about how users interact with the search engine, what they’re looking for, and more.

4] Relevancy Management

Search relevancy refers to how relevant the results are to the user typing the query. As every user is different with different requirements, not all results are relevant to all users. Enterprise search software today have relevancy management capabilities to ensure every user gets the most relevant results every time they interact with the software.

5] Content Integration

Content integration or data integration refers to the process of bringing together all the relevant information on a single platform, or connecting different locations where enterprise data is stored for easy access from a centralized location. With such large volumes of information that organizations handle today, data integration is a very useful functionality that an enterprise search software offers.

So, there are several different technologies that power the enterprise search software of today. Each of these have a key role to play in making a successful software.