ENTERPRISE SEARCH & CONTENT ANALYTICS BLOG

IntraFind experts provide there insights into the world of enterprise search, metadata extraction and usage as well as content analytics. Please feel free to share our blog with your colleagues or business partners.

- IntraFind Site Search as an alternative to Google Site Search (GSS)

Since April 1, 2018 Google Site Search is no longer available.  Website operators who cannot do without their search, can use IntraFind Site Search as a true replacement for GSS and benefit from many advantages.

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- Connectors - Hidden Success Factor for Universal Search

Single Source of Information. Is this the ultimate dream of all Enterprise Search Vendors, or is this reality about to happen? An approach by IntraFind's Product Manager Ralf Klinkhammer.

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- Content Delivery of Technical Information

Even nowadays technical documentation is mostly not valued as good or useful source of information. Too many incomprehensible or unmanageable documents have shaped the past and left behind frustrated or desperate users. Not to mention experts and technicians who prefer to rather trust their experience than long texts and inappropriate illustrations.

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- You don’t want to follow Google into the Cloud?
You don’t have to.

With the iFinder5 elastic IntraFind offers an interesting alternative to Google Search Appliance (GSA). If you need to extend GSA in your company or you want to switch to a future-proof and stable solution, the following blog post is just right for you.

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- Counting counts –
arguments for using statistics to process language

In this post I want to go a little deeper into Ludwig Wittgenstein's argument of "meaning is use" (Philosophical Investigations, 1953), and how it can be seen as a philosophical justification for statistical NLP, including machine learning.

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- Hardware was yesterday?
That’s right, we have always seen it this way.

Google recently announced to its Gold Partners that from 2017 on they no longer want to sell their Google Search Appliance, a hardware-software bundle that has been on the market since 2002. Google wants to solve this problem worldwide with a cloud-based application for companies. What is it all about the Google Search Cloud? Our idea for this is as follows.

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- Difficult Relations –
How Search Engines Can Be Expanded by Means of Word Families

What makes a good search engine? You type a sequence of letters and the document is searched for all occurrences of this combination. This way you can quickly and easily find certain text passages within a document. For a user who wants to find out more about a particular topic or the use of a particular word, such a basic search functionality would certainly not be enough.

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- New High Quality Search and Linguistics for iFinder5 elastic

IntraFind has long been known for high quality information retrieval. For our new product generation iFinder5 elastic we completely overhauled our core search technology consisting of our Lucene / Elasticsearch Analyzers and our Query Parser. In part 1 of this blog article I talk about advantages for the standard user and how we are able to reduce configuration efforts.

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- The iFinder5 elastic as Content Delivery Portal (CDP)

The launch of the new product generation iFinder5 elastic results in new use cases. One of them is "Content Delivery", which aims at the aspect of the application-specific and user-friendly supply of relatively static and - above all - quality assured information. Learn more about Content Delivery in Manuel Brunner´s blog post.

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- Language Identification and Language Chunking

Identifying the language of a given text is a crucial preprocessing step for almost all text analysis methods. It is considered as a solved problem since more than 20 years. Available solutions build on the simple observation that for all languages typical letter sequences (letter n-grams) exist, that occur significantly more frequent in this language than in other languages.

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- The difference between stemming and lemmatization

"Stemming" as well as "Lemmatization" are commonly used buzzwords in the field of Information Retrieval (IR), particularly in the development of powerful search engines. [...]

So what exactly is the difference between these two methods? What are the advantages and disadvantages and which one should be preferred? [...]

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- Approximative data structures for natural language processing

Some say software developers draw their motivation from minimizing or maximizing numbers in any given problem. That's a smug innuendo. From my experience, developers are always on the lookout for beautiful solutions, of which numbers are but a symptom. The usage of approximative data structures for language processing is one such example of a beautiful idea with nice numbers. [...]

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