IBM's Involvement With Open Source

Arnold, Stephen E.
September 2012
Online;Sep/Oct2012, Vol. 36 Issue 5, p42
Trade Publication
The author addresses the strong presence of the blue-chip company IBM in the open source software market. He cites the success of the company's mainframe computing products including its STorage and Information Retrieval System (STAIRS) and data mining functions. He also notes IBM's active involvement in the open-source search-and-retrieval systems Lucene and Solr.


Related Articles

  • Semantic Search Engine using Natural Language Processing. Pandiarajan, Sudhakar; Yazhmozhi, V. M.; Praveenkumar, P. // Australian Journal of Basic & Applied Sciences;2014 Special, Vol. 8 Issue 21, p36 

    The World Wide Web has become colossal and its growth is also dynamic. Most of the people rely on the search engines to retrieve and share information from various resources. All the results returned by search engines are not always relevant as it is retrieved from heterogeneous data sources....

  • Microsoft's Bing Search Wants to Strike Up a Conversation. Hernandez, Pedro // eWeek;8/14/2014, p5 

    The article discusses the effort of software company Microsoft Corporation to enhance user interaction with the Bing search engine. Topics included are the introduction of natural language capabilities for handling search entries conversationally, the initiative of lead developer Yan Ke to let...

  • Voice Recognition Arrives! Herther, Nancy K. // Searcher;Nov2011, Vol. 19 Issue 9, p20 

    The article focuses on voice recognition systems for consumers. It notes that voice recognition software have been used by several companies yet an industry around such product is forming to cater to mobile/consumer audiences and enterprise/web-level systems. Nuance Communications is cited as...

  • The Answer Machine Are We There Yet? Feldman, Susan // Searcher;Jan/Feb2011, Vol. 19 Issue 1, p18 

    The article discusses changes that have taken place in relation to online searching during the period of 2000 to 2010. The Web started to grow by 2000, leading to a rise in end-user searching. A decade after, valuable information has become freely available on the Web. Survey results indicate...

  • Next Generation Search Platforms: How Vendors are Searching Unstructured Content. Turner, Rich // Bulletin of the American Society for Information Science & Techn;Oct/Nov2009, Vol. 36 Issue 1, p16 

    The article explores three technologies that have found applicability in a number of business solutions which include natural language processing (NLP), Bayesian inference and latent semantic indexing (LSI) and analysis. It defines NLP as the best-known computer-based language technology. It...

  • A New Ontology-Based Semantic Similarity Algorithm in the Natural Language Processing. Xin-hua Zhu; Fang-fang Su; Qi-feng Tang // International Journal of Digital Content Technology & its Applic;Feb2012, Vol. 6 Issue 2, p188 

    Nowadays natural language processing can serve many useful tasks, such as helping design better search engines, better information retrieval, and rough summarization and rough translation of documents. In the natural language processing, all matching of existing concepts are based on semantic...

  • Mythbusting. Badke, William // Online Searcher;May/Jun2014, Vol. 38 Issue 3, p22 

    The article features myths that Internet services provider Google Inc. presents about information literacy. The author mentions the myths promulgated by Google Inc. that makes the jobs of librarians difficult include the simplicity of searching, the intent of users to have personalized results...

  • Automatic knowledge extraction for filling in biography forms from Turkish texts. PEHL─░VAN, ─░lknur; ORHAN, Zeynep // Turkish Journal of Electrical Engineering & Computer Sciences;2011, Vol. 19 Issue 1, p59 

    No abstract available.

  • A Comparative Study of Machine Learning Approaches- SVM and LS-SVM using a Web Search Engine Based Application. Arya, S. S.; Lavanya, S. // International Journal on Computer Science & Engineering;May2012, Vol. 4 Issue 5, p816 

    Semantic similarity refers to the concept by which a set of documents or words within the documents are assigned a weight based on their meaning. The accurate measurement of such similarity plays important roles in Natural language Processing and Information Retrieval tasks such as Query...


Read the Article


Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics