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Social job search


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Social job search

  1. 1. Silvestri - VesciApril 24, 2012 1
  2. 2. Expert Finding in CrowdSearching CrowdSearcher involves users belonging to a trusted network, to answer complex queries. Expertise Retrieval in the context of CrowdSearcher  What  When  Who: CrowdSearcher should automatically redirect the query to the set of users that have a good knowledge of the questions’s topic.  Where: It also should do it in the best social network, where the crowd user has more probability to answer. 2
  3. 3. Architecture •Crawling social network Resources through REST API •Enriching Resources and Query with Semantic Data (entities, categorization) using a combination of tools: AlchemyAPI, TagMe, Open Calais… •Storing and Indexing •Matching : How ? 3
  4. 4. Future experiments Matching method: candidate model vs resource model A model M(ca) is inferred for each Resources are analyzed and candidate ca from his resources queried. The candidates and profile. The model is then used associated with each resource are to predict how likely a candidate then considered as possible would produce a query q. experts. Analysis of social graph: Retrieve better results studying the network of contacts. 4
  5. 5. A Case study: Social Job Search Automatically search best candidates to a job offer. Instances: • Candidates are users that have provided permissions to access to their social network information • Companies send job offers, expecting a list of compatible users as result • Experts manually select a smaller list of users from the set originally returned by the system 5
  6. 6. Conclusions Need for data: We have developed a website in order to obtain users with which test our research. It is possible to add • Facebook • LinkedIn • Twitter • Curriculum Vitae eventually moving to Dbgroup SeCo Server 6