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Things, not strings

Things, not strings
Cross-posted on the Inside Search Blog Search is a lot about discovery—the basic human need to learn and broaden your horizons. But searching still requires a lot of hard work by you, the user. So today I’m really excited to launch the Knowledge Graph, which will help you discover new information quickly and easily. Take a query like [taj mahal]. For more than four decades, search has essentially been about matching keywords to queries. To a search engine the words [taj mahal] have been just that—two words. But we all know that [taj mahal] has a much richer meaning. The Knowledge Graph enables you to search for things, people or places that Google knows about—landmarks, celebrities, cities, sports teams, buildings, geographical features, movies, celestial objects, works of art and more—and instantly get information that’s relevant to your query. Google’s Knowledge Graph isn’t just rooted in public sources such as Freebase, Wikipedia and the CIA World Factbook. 1. 2. 3.

Improved Tools for Driving Search, Journalism, and Content Strategy | Mojo40 Keywords are out! Kaput! Passé! Semantic search is in. Just as Rosie used a paper towel that was a “quicker picker upper,” digital search has become more exact by using semantic search technology. On May 16, Mashable reported that Google search would no longer be based on keywords in a search string, but on a much more refined understanding of how language is used. Semantic search uses a deeper understanding of the relationship between words and the intent of the searcher, so when you type in something on a search engine or on a closed loop system (like that found in an enterprise), the underlying software examines the broader meaning, digests it, and spits back results that are much more relevant. Semantic technology is a subject touched on in a previous post profiling an education start-up, but it deserves a deeper dive. According to the Gilbane Group, semantic software technology has led to a wide variety of improvements in: Mojo40: What do you offer that is new? Related posts:

6 Gorgeous Facebook Visualizations Like every complex network, Facebook offers unlimited possibilities of visual representation of the various connections between its users. We've chosen six beautiful visualizations that will awaken the (visual) geek within you. You don't have to stop at merely watching. Know of a beautiful Facebook visualization? 1. This project visualizes all the data Facebook receives, on a global scale. 2. This wonderful illustration, created by Lee Byron from the Facebook data team, shows how Facebook has evolved from being a social network for universities to the global social networking powerhouse it is today, with over 200 million users. 3. Friend Wheel is a simple Facebook application that creates a radial graph out of all your Facebook friends. 4. This Java based application lets you see the connections between your Facebook friends, with emphasis on photos; i.e., you can see which friends have taken photos together. 5. Still images really don't do justice to this one. 6.

Google Launches Knowledge Graph To Provide Answers, Not Just Links Hinted at for months, Google formally launched its “Knowledge Graph” today. The new technology is being used to provide popular facts about people, places and things alongside Google’s traditional results. It also allows Google to move toward a new way of searching not for pages that match query terms but for “entities” or concepts that the words describe. Knowledge Graph? “Graph” is a technical term used to describe how a set of objects are connected. Big Change, Subtle Appearance Earlier this year, the Wall Street Journal wrote about the coming change. Big change, but I don’t think it’ll be a shocking change to most Google users who will begin seeing it over the coming days on Google.com, if they’re searching in US English. Google will still look largely the same as it does now. Knowledge panels don’t always appear, only showing up only when Google deems them relevant. Fact Surfing 3.5 Billion Facts About 500 Million Objects Again, those are just some of the categories. Fixing Bad Data

Entrepreneur Gaurav Mittal led ITCONS will introduce Intelligent concept search based on Semantics Technology for Recruitment Industry Entrepreneur Gaurav Mittal led ITCONS will introduce Intelligent concept Search based on Semantics Technology in January 2010, a first of its kind in India. Current product portfolio of ITCONS comprises of SaaS based Online Resume Parser & Applicant Tracking System. While the international markets are talking about Monster.com’s recent launch of Power Resume Search based on semantics (a technology which helps scan resumes and job openings for better matching) in the US provided by a company called Trovix, which was acquired by Monster or a cash prize of $72.5 millions last year. Delhi based entrepreneur Gaurav is set to launch prototype of ICS (Intelligent Concept Search) in January ‘2010, which is similar to one provided by Trovix. ICS will work with any Online Job Portals/ with any ATS/ HR applications of any company to provide advanced searching and matching capabilities between a source document and candidates. Use resumes /CVs as source document: Traditional Search Approach

Facebook Graph Search Review, How it Works Social Media Examiner Facebook recently announced Graph Search. In this article I’ll share what Facebook’s Graph Search is, how it works and how it fits your marketing strategy. What Is Graph Search? Graph Search is Facebook’s latest revision to the search feature that helps users find connections to people and places that have always existed in the graph. In a sense, it’s a clean interface into the breadth of Facebook data that people have entered into Facebook, but contextualized to each user. Watch this video introducing Facebook Graph Search. Think about that for a moment. Kudos to the Facebook engineering team for this major achievement. As you’ll see below, it’s early for Graph Search. But this first version gives us clues about how Facebook may evolve and the strengths on which they’ll try to build. Walkthrough of Facebook Graph Search Let’s start with a search about one of my favorite foods—bacon! In the screenshot below, you can see a search for “bacon” in the old Facebook search format. Who knew? 1. 2. 3.

Knowledge Graph : Google officialise son moteur sémantique Les règles du jeu semblent distribuées depuis quelques jours entre les deux géants du search : Bing se lance dans le social tous azimuths, aidé par ses relations étroites avec Facebook et Twitter. Google, limité par le succès trop faible de son réseau Google+, se tourne - pour l'instant - vers d'autres voies d'innovation et intègre de plus en plus de sémantique dans ses résultats. Déjà en phase de test depuis plusieurs mois, ces fonctionnalités ont été annoncées officiellement par Google sous le nom de "Knowledge Graph". Cette nouvelle vision permet d'obtenir de très nombreux renseignements sur les "entités nommées" (noms de personnes, d'entreprises, de lieux, etc.) contenues dans la requête de l'internaute. Le "Knowledge Graph" sera présent dans les pages de résultats de Google, au fur et à mesure des semaines qui viennent, sous 3 formes différentes : - Désambigüisation de la requête demandée. - Propositions de liens pour en savoir plus sur des sujets proches de celui recherché :

Text analytics / June | Volume 39 | Number 3 / Public Articles / ORMS-Today / IOL Home - INFORMS.org By Douglas A. Samuelson New computer software and analytical methods offer promising ways to combine two kinds of data traditionally separated: quantitative and qualitative information. What data mining became in the 1990s, text mining/text analytics may well become in the current decade – a powerful way to find patterns not previously suspected. Statistical analysis and understanding natural language can go together. New methods and technology now make it possible to store, index, search and retrieve free-form text more effectively and efficiently, and on a much larger scale, than was possible just a few years ago. Buoyed by these advances, text mining offers great promise for OR/MS and general analytics. Computerized storage and keyword-based retrieval of free-form text is not new. In 1991, this reporter applied text-mining methods to demonstrate the ability to detect and discover patterns of causation in general aviation crashes [5]. Expanding the Method: Key Definitional Questions

This Is The Social Graph Explained La recherche passe à l’ère sémantique (et sociale) (et pas visuelle) La semaine dernière, la frénésie autour de l’IPO de Facebook était a son apogée et qui a fait passé presque inaperçu un changement majeur pour le web : l’évolution du fonctionnement de la recherche de Google (Introducing the Knowledge Graph: things, not strings). Google à l’assaut du web sémantique avec son Knowledge Graph La raison majeure de cette évolution est la prise en compte de données sémantiques dans les résultats de recherche. Le principe est le suivant : plutôt que se fier à des chaînes de caractères, Google va maintenant travailler à partir de données structurées (“Things, not strings“). Ces données structurées sont la résultante des travaux de sémantisation des contenus initiés par les équipes de Google il y a de nombreuses années qui avaient déjà permis de faire des premières expérimentations (notamment la roue magique qui depuis a été mise hors ligne : Google Knowledge Graph, un pas vers la recherche sémantique). Présenté de cette façon, ça à l’air très bien. Yahoo!

Web Graph Database (This excellent overview was written by Woody Pidcock of the Boeing company and posted at metamodel.com. It has been edited slightly so it could be archived here.) I will answer this question one step at a time. To keep this answer focused on the question, I will use other concepts that I will not define here. A controlled vocabulary is a list of terms that have been enumerated explicitly. This list is controlled by and is available from a controlled vocabulary registration authority. If the same term is commonly used to mean different concepts in different contexts, then its name is explicitly qualified to resolve this ambiguity. A taxonomy is a collection of controlled vocabulary terms organized into a hierarchical structure. A thesaurus is a networked collection of controlled vocabulary terms. People use the word ontology to mean different things, e.g. glossaries & data dictionaries, thesauri & taxonomies, schemas & data models, and formal ontologies & inference. Additions ¶

‎www.steigmancommunications.com/2013/08/05/what-you-need-to-know-about-twitters-interest-graph/ Have you seen the AT&T ad where little kids posit numbers bigger than infinity? (The ad is awesome, by the way.) These days, some social media platforms have their own versions of crazy numbers. A few examples: Google : le 'Knowledge Graph' génère plus de requêtes... et de publicités Abondance > Actualités > Google : le 'Knowledge Graph' génère plus de requêtes... et de publicités Google a indiqué que depuis le lancement de l'application sémantique Knowledge Graph sur son moteur de recherche, le nombre de requêtes avait augmenté de façon importante. En effet, Amit Singhal, l'une des principales têtes pensantes de l'algorithme de Google, l'a indiqué dans le Wall Street Journal, information confirmée par le service de presse du moteur. Cela est logique dans le sens où le "Knowledge Graph" propose de nombreux liens concernant l'objet de la requête et de l'"entité nommée" détectée. D'ailleurs, cela pourrait clairement être à l'avantage de Google : l'internaute tape une requête sur la page d'accueil du moteur, obtient les résultats du Knowledge Graph, reclique sur les liens de recherche proposés, etc. Bref, qui est le gagant de cette nouveauté sémantique ?

Realmatch Job Search | Job Match -TJNSRV01 RealMatch uses unique Real-Time Job Matching technology. This means that you no longer have to use antiquated keyword search to find a job. You simply enter your skills and preferences, find perfectly matching jobs, explore career opportunities all the while remaining anonymous. In addition, RealMatch is based on a network of thousands of partner sites from a variety of locations and industries. This means that you will receive a great variety of job matches from the locations and occupations of your choice. RealMatch does not ask you to submit your name, address or any other indentifying details. RealMatch is using three elements to create a job match: your skills, your job preferences and the job requirements. Skills and preferences can be added in the “My Match Profile” tab. Job Matches are ranked according to: Great Matches, Good Matches or Basic Matches. RealMatch is unique in its ability to match you with a job based on specific job titles that you are interested in.

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