The previous posts on short summaries from each of the presentations from the meeting can be found for Day 1 and Day 2. This final post of the 2013 II-SDV meeting will provide the full list of tweets associated with the meeting.
Copies of the presentations can be found here.
@atripper Li – discussing the analysis of graphic elements (images) from patent documents using TRIZ techniques #iisdv13
@atripper Zheng Li – School of Engineering and Design, Brunel University – A Top-Down Method of Patent Mapping #iisdv13
@atripper Stellmach – Discussing the Problem Solution Approach (PSA) for determining inventive step for examining European patents #iisdv13
@atripper Joachim Stellmach – European Patent Office – Graphical Representation of the Assessment of Inventive Step for Patent Applications #iisdv13
@atripper Kirk – Five layers of a visualization – spatial, color, interactivity, annotation, and arrangement #iisdv13
@atripper Kirk – building visualizations – are your going to be pragmatic or analytical or more emotive or aesthetic connection #iisdv13
@atripper Kirk – building visualizations – are you telling a story or do you expect the user to find their own story? #iisdv13
@atripper Kirk – when building visualizations start with asking what is the purpose, or what was the trigger and intent of it #iisdv13
@atripper Andrew Kirk – Visualizing Data – Finding Stories and Telling Stories: Two Sides of Data Visualization #iisdv13
@atripper Webb – multiple sources of clinical trial data are necessary to provide a complete picture in a field #iisdv13
@atripper Webb – BizInt working on a “Bulls-Eye” chart which combines clinical stage with therapeutic area to display individual drugs #iisdv13
@atripper Webb – cleaning up & prioritization of clinical trial stages is necessary & valuable to provide accurate info to pharma #iisdv13
@atripper Diane Webb – BizInt Solutions – Challenges in Visualizing Pharmaceutical Business Information #iisdv13
@atripper Hofmann-Apitius – scoring function for BEL statements used to determine statistical reliability of disease networks #iisdv13
@atripper Hofmann-Apitius – BEL roughly correlates to Subject-Action-Object triplets and helps identify disease relationships #iisdv13
@atripper Hofman-Apitius – Discussing the development of the BEL ontology for disease models based on text-mining #iisdv13
@atripper Hofmann-Apitius – BEL stands for Biological Expression Language for disease relationships #iisdv13
@atripper Martin Hofmann-Apitius – Fraunhofer – Text Mining at Work: Critical Assess of Complete & Correct of Knowledge-Based, Disease Models #iisdv13
@atripper Milward – using linguistics followed by statistical methods to provide higher level of precision & recall in text mining #iisdv13
@atripper Milward – text mining can be used for drug repurposing by looking for associations between substances and genes and enzymes #iisdv13
@atripper Milward – Twitter content can be messy but it often provides for interesting patterns when analyzed linguistically #iisdv13
@atripper Milward – working with linguistic units as opposed to proximity can provided higher precision and recall in searching #iisdv13
@atripper David Milward – Linguamatics – Text Mining Diverse Data #iisdv13
@atripper Parthasarathy – Keys to Social Media success – Start early, start smart (be engaging) and don’t stop #iisdv13
@atripper Parthasarathy – Therapy pages, as opposed to company pages provide higher ROI, customers engage on use rather than brand #iisdv13
@atripper Parthasarathy – Pharma’s popularity is higher on Facebook but it is more influential on Twitter #iisdv13
@atripper Parthasarathy – Starting early with developing a social media presence is a key indicator for eventual success #iisdv13
@atripper Parthasarathy – SAARAA Medical Solutions – Pharmaceutical Companies and Social Media: Developing New Strategies #iisdv13
@atripper Parthasarathy – With twitter content is more important than volumn for generating engagement and trust on the system #iisdv13
@atripper Newman – small amount of legitimate technical content coming from tweets as well as some business context information #iisdv13
@atripper Newman – One of the key questions regarding twitter mining is who are the key thought-leaders in an area #iisdv13
@atripper Nils Newman – Search Technology / Vantage Point – Tweet Mining: Is it Useful and Should we Bother #iisdv13
@atripper Kury – journals are no longer routed at Novartis but newsletters are generated with the TOCs of key journals #iisdv13
@atripper Kury – Tier 3 is called customized solutions and are maintained by internal consultants and aggregates data from many sources #iisdv13
@atripper Kury – Tier 2 for current awareness involves the information professional and uses commercial vendors managed by info pro #iisdv13
@spinque @atripper thanks for tweeting #iisdv13 – very interesting!
@atripper Kury – Current awareness is organized by tiers, tier 1 revolves around end-user needs and tools and is mostly driven by user #iisdv13
@atripper Dieter Kury – Novartis Pharma – Customized Newsletters – Strategies to Improve Current Awareness #iisdv13
@atripper Fischer – Sygenta group doing a fabulous job of extending the need for technology mining to new business clients #iisdv13
@atripper Fischer – Process involves search retrieval, normalization and visualization and analysis #iisdv13
@atripper Fischer – People, Process and Tools need to be initimately integrated for success in the tech mining space #iisdv13
@atripper Fischer – Skills required for Technology Miner – Adaption to IT, understand mining process, ability to sell capabilities #iisdv13
@atripper Fischer – Technology mining is having an impact on all areas of business including acquisitions and strategy #iisdv13
@atripper Fischer – Freedom to Operate and Technology Mining represent majority of work being conducted by information services group #iisdv13
@atripper Gerhard Fischer – Syngenta – Key Success Factors in the Setup of Cutting-Edge Patent Intelligence Services #iisdv13
@atripper Archambeault – not just about information retrieval but also about content processing for the users needs #iisdv13
@atripper Archambeault – Expectations 4 text analytics – sentiment analysis, Subject Action Object triplets & relationship visualiz #iisdv13
@atripper Archambeault – used a collection of 72 metrics with different weightings to evaluate the systems they considered #iisdv13
@atripper Archambeault – Looking to go beyond a simple feed of data and provide intelligence and the ability to anticipate trends #iisdv13
@atripper Archambeault – Looking for means to analyze unstructured text and social media output towards supporting alerting services #iisdv13
@atripper Jean Archambeault – National Research Council, Canada – In Search of an Environmental Monitoring Tool #iisdv13
@atripper Gabery – created selective filters and means of generating templates for presenting data to different client segments #iisdv13
@atripper Gabery – used funding simulation to prioritize 11 different ideas being suggested by information innovation group #iisdv13
@atripper Solmaz Gabery – Novo Nordisk – Challenges in Building a Future Search Centre – Observations and Choices #iisdv13
@atripper Gautier-Hamel – Web 2.0 technology like LinkedIn can be key sources for CI, Digimind is also good for web mining #iisdv13
@atripper Gautier-Hamel – Challenges include working with non-patent literature as well as patents, also interested in identifying start-ups #iisdv13
@atripper Natalie Gautier-Hamel – Lafarge – Challenge of Finding and Using Tools for Competitive Intelligence in Construction & Materials #iisdv13
@atripper Rozenberg – Demonstrated specific steps required to identify patents that have been reassigned to known and unknown NPEs #iisdv13
@atripper Ed Rozenberg – Dolcera – Automating Web Research through Customized Search Tools #iisdv13
@atripper Hawking – Query suggestion, faceted navigation, result diversification & presentation are result based approaches 2 query building #iisdv13
@atripper David Hawking – Funnelback – Searching within the Enterprise: Making the Best User Queries #iisdv13
@atripper Dietrich – Rule based classifications are accurate but recall is low, the machine learning methods were used instead #iisdv13
@atripper Dietrich – used Averbis for the fine-grained patent classification for the project, used 80 categories #iisdv13
@atripper Dietrich – Overall Process – Scope Definition, Patent Search, Data Normalization and Classification & Visualization #iisdv13
@atripper Dietrich – generated patent indicators and technology classifications for the IP portfolios of 15 competitors #iisdv13
@atripper Manuel Dietrich – Roche Diagnostics – Large Scale Patent Landscaping – Experiences and Lessons Learned #iisdv13
@Treparel Advanced treemap visualization of the full #iisdv13 agenda and speakers of this weeks conference in Nice: http://www.ii-sdv.com/viz/htree3.html #bigdata
@Treparel Dr. Anton Heijs talks about EU http://Fusepool.net : A Large Scale Application of Text Mining and Visualization @iisdv13 #bigdata
@atripper Garat – customization can be time consuming but investment can be worth it if they can be reapplied to other projects #iisdv13
@atripper Renaud Garat – Questel – Customizing Statistics for Sharper Analysis #iisdv13
@atripper Kearns – Suggests starting with business need and working backwards to data and analytics is key – been saying for decades #iisdv13
@atripper Kearns – Big Data Processing – Collect, Analyze and Index, the three steps required for this process #iisdv13
@atripper Steve Kearns – Basis Technology – Big Data Triage with Text Analytics #iisdv13
@atripper Heijs – Fusepool looking at patent analysis, funding opportunities and finding partnerships #iisdv13 – fusepool.eu
@atripper Heijs – main focus of Fusepool is SWOT analysis for small to medium size companies who need to understand their environment #iisdv13
@atripper Heijs – EU project is called Fusepool which stands for Fusing and Pooling Information for Product Development #iisdv13
@atripper Anton Heijs – Treparel – Large scale application of text mining & visualization in the EU Fusepool project #iisdv13
@atripper Governments around the world are moving towards posting their data openly for third-party vendors to add value to #iisdv13
@atripper R, Weka and Apache Mahout are analytics packages which are used with Hadoop on Big Data #iisdv13
@atripper Only a matter of time before most database applications migrate to Hadoop, especially with big data #iisdv13
@atripper Patrick Beaucamp – BPM-Conseil – Open Source Platforms to deploy search and Maps Visualiz on top of big database #iisdv13
@atripper The use of graphics processing units (GPUs) will have a major impact on the semantic processing in the next few years #iisdv13
@atripper Greater than 50% of tweets are machine-generated as opposed for a particular agenda #iisdv13
@atripper I will be live tweeting from II-SDV in Nice, France for the next two days – #iisdv13
@atripper Starting with Roger Bradford – Agilex – Analytic Challenges Posed by Big Data #iisdv13
