Update from Lucene
May 10, 2016
It has been awhile since we heard about our old friend Apache Lucene, but the open source search engine has something new, says Open Source Connections in the article, “BM25 The Next Generation Of Lucene Relevance.” Lucene is added BM25 to its search software and it just might improve search results.
“BM25 improves upon TF*IDF. BM25 stands for “Best Match 25”. Released in 1994, it’s the 25th iteration of tweaking the relevance computation. BM25 has its roots in probabilistic information retrieval. Probabilistic information retrieval is a fascinating field unto itself. Basically, it casts relevance as a probability problem. A relevance score, according to probabilistic information retrieval, ought to reflect the probability a user will consider the result relevant.”
Apache Lucene formerly relied on TF*IDF, a way to rank how users value a text match relevance. It relied on two factors: term frequency-how often a term appeared in a document and inverse document frequency aka idf-how many documents the term appears and determines how “special” it is. BM25 improves on the old TF*IDF, because it gives negative scores for terms that have high document frequency. IDF in BM25 solves this problem by adding a 1 value, therefore making it impossible to deliver a negative value.
BM25 will have a big impact on Solr and Elasticsearch, not only improving search results and accuracy with term frequency saturation.
Whitney Grace, May 10, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
An Open Source Search Engine to Experiment With
May 1, 2016
Apache Lucene receives the most headlines when it comes to discussion about open source search software. My RSS feed pulled up another open source search engine that shows promise in being a decent piece of software. Open Semantic Search is free software that cane be uses for text mining, analytics, a search engine, data explorer, and other research tools. It is based on Elasticsearch/Apache Solrs’ open source enterprise search. It was designed with open standards and with a robust semantic search.
As with any open source search, it can be programmed with numerous features based on the user’s preference. These include, tagging, annotation, varying file format support, multiple data sources support, data visualization, newsfeeds, automatic text recognition, faceted search, interactive filters, and more. It has the benefit that it can be programmed for mobile platforms, metadata management, and file system monitoring.
Open Semantic Search is described as
“Research tools for easier searching, analytics, data enrichment & text mining of heterogeneous and large document sets with free software on your own computer or server.”
While its base code is derived from Apache Lucene, it takes the original product and builds something better. Proprietary software is an expense dubbed a necessary evil if you work in a large company. If, however, you are a programmer and have the time to develop your own search engine and analytics software, do it. It could be even turn out better than the proprietary stuff.
Whitney Grace, May 1, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Elasticsearch Works for Us 24/7
February 5, 2016
Elasticsearch is one of the most popular open source search applications and it has been deployed for personal as well as corporate use. Elasticsearch is built on another popular open source application called Apache Lucene and it was designed for horizontal scalability, reliability, and easy usage. Elasticsearch has become such an invaluable piece of software that people do not realize just how useful it is. Eweek takes the opportunity to discuss the search application’s uses in “9 Ways Elasticsearch Helps Us, From Dawn To Dusk.”
“With more than 45 million downloads since 2012, the Elastic Stack, which includes Elasticsearch and other popular open-source tools like Logstash (data collection), Kibana (data visualization) and Beats (data shippers) makes it easy for developers to make massive amounts of structured, unstructured and time-series data available in real-time for search, logging, analytics and other use cases.”
How is Elasticsearch being used? The Guardian is daily used by its readers to interact with content, Microsoft Dynamics ERP and CRM use it to index and analyze social feeds, it powers Yelp, and her is a big one Wikimedia uses it to power the well-loved and used Wikipedia. We can already see how much Elasticsearch makes an impact on our daily lives without us being aware. Other companies that use Elasticsearch for our and their benefit are Hotels Tonight, Dell, Groupon, Quizlet, and Netflix.
Elasticsearch will continue to grow as an inexpensive alternative to proprietary software and the number of Web services/companies that use it will only continues to grow.
Whitney Grace, February 5, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
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