Summer Intern/Information Extraction and Integration

inome is gathering the world’s information and making it people centric. The inome graph connects billions of entities (people,organizations and addresses) to encode the information-genome of each  individual. inome Research is looking for graduate interns to work on developing its next generation of Information Extraction and Information Integration technologies. The interns for summer 2013 will  explore developing novel strategies for extracting intelligence from both unstructured text and semi-structured text and integrating the
intelligence with the inome graph. Sample projects include extracting  events, trends, users' interests from unstructured text; extracting attributes of people from publicly available sources; linking  extracted entities to the entity nodes in the inome graph. This is likely to be innovative work and we expect the summer internship to lead to both product impact and a research paper in a top conference.  The internship will be at our headquarters in Bellevue, WA, and offer a competitive compensation.

inome Research develops cutting-edge systems to standardize, create,
and link intelligence to power inome's industry-leading people
information-genome platform. Team members have published papers in top
research conferences such as NIPS, ACL, VLDB, CIKM, and SIGIR, given
invited talks, organized workshops, and turned algorithms into
deployed systems.

Responsibilities:

    Build and/or extend systems to do high-precision IE from
structured, semi-structured, and unstructured information sources
    Build and/or extend systems to do high-precision linkage from a
variety of information sources
    Design and implement algorithms for evaluating the performance of
IE and linkage

Required Skills:

    Graduate student working on a Ph.D. in Natural Language
Processing, Data Mining, Computational Social Science or related field
    Experience in one or more of the following areas: named entity
extraction, relation extraction, within document and cross-document
coreference, graph-based information extraction and information
fusion/integration
    Self-motivated, creative, and independent researching skills

Desired Skills:

    Strong hands-on skills in Java
    Experience with large-scale machine learning
    Experience with Hadoop
    Familiarity with graph based machine learning toolkits such as GraphLab
    Experience with crowdsourcing/Mechanical Turk
    Experience with NLP toolkits
    Experience with supervised/semi-supervised/

unsupervised
information extraction
    Experience with graph-based NLP

Contact:
Please apply online. For faster considerations, please send your CV to
Ang Sun, asun@inome.com