background preloader

Opinion Crawl - sentiment analysis tool for the Web and social media

Opinion Crawl - sentiment analysis tool for the Web and social media
Related:  Contextual/Semantic Search Engines

Real-Time Sentiment Analysis To ensure greater customer satisfaction, you must first understand how your customers feel about your company. And it’s all in the details. HP Autonomy delivers next-generation sentiment analysis—granular, specific, and accurate—performed on all types of content, including social media. With HP IDOL, you can determine the degree to which a sentiment is positive, negative, or neutral for the entire content set or a segment of the content. In addition, administrators can also apply multiple tagging functions and specific threshold cut-offs to determine the sensitivity of sentiment analysis. IDOL uses both linguistic analysis and a statistical, pattern-based approach to derive sentiment. Understand sentiment at a granular level: IDOL can detect sentiment at a sub-sentence level so that if a sentence consists of mixed feelings (e.g., Loved the service but didn’t care for the food), you can extract each concept and its associated sentiment.

OWL The OWL Web Ontology Language is designed for use by applications that need to process the content of information instead of just presenting information to humans. OWL facilitates greater machine interpretability of Web content than that supported by XML, RDF, and RDF Schema (RDF-S) by providing additional expressive power along with a formal semantics. The group's work is complete with the publication of OWL 2 (Second Edition). There may be new Errata and discussion on Second Edition Deliverables See Documentation Roadmap for more details First Edition Deliverables Editors' Drafts (Wiki) Inputs Membership Charter, Meeting Records, and History The OWL Working Group Charter shows what the W3C has asked this working group to do. W3C Working Group Resources OWL 1.0 Resources Staff

OWL - Semantic Web Standards Overview The W3C Web Ontology Language (OWL) is a Semantic Web language designed to represent rich and complex knowledge about things, groups of things, and relations between things. OWL is a computational logic-based language such that knowledge expressed in OWL can be exploited by computer programs, e.g., to verify the consistency of that knowledge or to make implicit knowledge explicit. The current version of OWL, also referred to as “OWL 2”, was developed by the [W3C OWL Working Group] (now closed) and published in 2009, with a Second Edition published in 2012. Recommended Reading As can be seen from the above mentioned Documentation Roadmap, OWL 2 is normatively defined by five core specification documents describing its conceptual structure, primary exchange syntax (RDF/XML), two alternative semantics (Direct and RDF-Based), and conformance requirements. These documents are, however, all rather technical and mainly aimed at OWL 2 implementers and tool developers. All relevant tools

9th Extended Semantic Web Conference (ESWC), Heraklion 2012 - VideoLectures The Extended Semantic Web Conference (ESWC) is a major venue for discussing the latest scientific results and technology innovations around semantic technologies. Building on its past success, ESWC is seeking to broaden its focus to span other relevant research areas in which Web semantics plays an important role. The goal of the Semantic Web is to create a Web of knowledge and services in which the semantics of content is made explicit and content is linked to both other content and services novel applications allowing to combine content from heterogeneous sites in unforeseen ways and support enhanced matching between users needs and content. This network of knowledge-based functionality will weave together a large network of human knowledge, and make this knowledge machine-processable to support intelligent behaviour by machines. Detailed information can be found at ESWC 2012 website.

Natural Language Toolkit — NLTK 2.0 documentation Search » semantic web search Top 225 results of at least 6,400,000 retrieved for the query semantic web search ( details ) These sources have been queried: - Top results retrieved out of in seconds. - No results retrieved in seconds. - No results retrieved in seconds. - No results retrieved in seconds. - Top results retrieved out of in seconds. - No results retrieved in seconds. - No results retrieved in seconds. - No results retrieved in seconds. - Top results retrieved out of in seconds. - Top results retrieved out of in seconds. ads go here I just stumbled upon a useful resource from Sindice (the Semantic Web search engine) called the Map of Data. For example, the search for gives enough to answer what is the Semantic Web . ... Abstract Activities such as Web Services and the Semantic Web are working to create a web of distributed machine understandable data. Pandia reviews the best search engines on the web using semantic search technologies. Semantic Search and the Semantic Web are often confused.

Semantic Search in 2025 Tim Berners-Lee first spoke of a Semantic Web at his address at the first World Wide Web Conference in 1994. Given the technical level of the audience, his presentation was, for the most part, met with excited nods. The Web Berners-Lee described was a far cry from the library-style repository of the Web at that time, but the concept wasn't so far-fetched, at least to the listeners with a more visionary nature. "Semantic", however, is a qualifier that means a great deal in this context. It demands that a machine, or more accurately, the software that drives that machine, must understand the information in the way it was intended. Indeed, for a machine to comprehend the meaning behind what a human has put to text, requires a certain amount of artificial intelligence. The Other Approach Enter: semantic mark-up, such as RDFa, microformats, microdata, structured data. Syntactic and Semantic Graphs Rudimentary, perhaps, but still pertinent. Similarly, many rules (a great many!)

Clustering Engine Carrot2 Search Results Clustering Engine Carrot2 organizes your search results into topics. With an instant overview of what's available, you will quickly find what you're looking for. Choose where to search: Type your query: More options More advanced options Hide advanced options Example queries: data mining | london | clustering About Carrot2: Carrot2 is an Open Source Search Results Clustering Engine.

Breakthrough Analysis: Two + Nine Types of Semantic Search - Software There's more to it than offering related results. Here are 11 approaches that join semantics to search. Semantics is hot, but only in a geeky sort of way. Contrast with search, which long ago shed its geeky image to become the Web's #1 utility. Semantic search is still in a definitional phase, "on its way!" Semantics (in an IT setting) is meaningful computing: the application of natural language processing (NLP) to support information retrieval, analytics, and data-integration that compass both numerical and "unstructured" information. I've come up with a list of eleven approaches that join semantics to search: my two Bing-ers plus nine more. Two + Nine Views of Semantic Search Related searches/queries. A quick announcement of a conference I'm organizing: The 2010 Sentiment Analysis Symposium will take place April 13 in New York, looking at solutions that discover business value in opinions and attitudes in social media, news, and enterprise feedback. More Insights - The Voice of Semantic Web Business 9 Semantic Search Engines That Will Change the World of Search The ideal search engine would be able to match the search queries to the exact context and return results within that context. While Google, Yahoo and Live continue to hold sway in search, here are the engines that take a semantics (meaning) based approach, the end result being more relevant search results which are based on the semantics and meaning of the query, and not dependent upon preset keyword groupings or inbound link measurement algorithms, which make the more traditional search engines easier to game, thus including more spam oriented results. Here is a wrap up of some of the top semantic search engines which we’ve covered previously, and some updates on their research. 1. Hakia The brainchild of Dr. The search queries are mapped to the results and ranked using an algorithm that scores them on sentence analysis and how closely they match the concept related to the query. Hakia semantic search is essentially built around three evolving technologies: Hakia Lab 2. 3. 4. 5. 6. 7. 8.

Semantic search Guha et al. distinguish two major forms of search: navigational and research.[3] In navigational search, the user is using the search engine as a navigation tool to navigate to a particular intended document. Semantic search is not applicable to navigational searches. In research search, the user provides the search engine with a phrase which is intended to denote an object about which the user is trying to gather/research information. Rather than using ranking algorithms such as Google's PageRank to predict relevancy, semantic search uses semantics, or the science of meaning in language, to produce highly relevant search results. Disambiguation[edit] Such processes make use of other information present in a semantic analysis system and takes into account the meanings of other words present in the sentence and in the rest of the text. Every node of the network (called Synset) groups a set of synonyms which represent the same lexical concept (called Synsets) and can contain: