GSB'15: First International Workshop on Graph Search and Beyond

Call for Papers

Please submit your Research/Position Paper (3+1 pages) to be presented as boaster and poster at the workshop!

Graph Search and Beyond

Information on the Web is increasingly structured in terms of entities and relations from large knowledge resources, geo-temporal references and social network structure, resulting in a massive multidimensional graph. This graph essentially unifies both the searcher and the information resources that played a fundamentally different role in traditional IR, and offers major new ways to access relevant information. In services that rely on personalized information like social networks, the graph plays an even more important role, in other words: you are the query.

Graph search affects both query formulation as well as result exploration and discovery. On the one hand, it allows for incrementally expressing complex information needs that triangulate information about multiple entities or entity types, relations between those entities, with various filters on geo-temporal constraints or the sources of information used (or ignored), and taking into account the rich profile and context information of the searcher (and his/her peers, and peers of peers, etc). On the other hand, it allows for more powerful ways to explore the results from various aspects and viewpoints, by slicing and dicing the information using the graph structure, and using the same structure for explaining why results are retrieved or recommended, and by whom.

Many Open Questions

We view the notion of ``graph search'' as searching information from your personal point of view (you are the query) over a highly structured and curated information space. This goes beyond the traditional two-term queries and ten blue links results that users are familiar with, requiring a highly interactive session covering both query formulation and result exploration, and raises many open questions:

• IR Theory: What happens if search gets personal? Does this break the classic dichotomy between users and documents, as users are nodes in the social network data themselves? What is the consequence of ultimate personalization, as the local graph differs for all users? As the local graph structure is key, does this obviate the need for large central indexes? Do these types of requests fit in the classic paradigm (e.g., Broder's taxonomy)? How does this shift the balance between the control of the searcher and the ranker over the result set?
• Data Integration: Building a knowledge graph requires massive data integration at many levels: are there trade-offs in simplicity and level of detail (such as the classic knowledge representation trade-off)? What levels of granularity and comprehensiveness are needed for effective deployment? What quality is needed: is any noise acceptable? How to deal with near duplicate detection, conflation, or entity disambiguation?
• Use Cases and Applications: Rather than a universal solution, graph search is particularly useful for specific types of information needs and queries. What are the data and tasks that make graph search works? What kind of scenarios that would benefit from a graph model? In what context can switching perspectives by showing results from the vista of other persons useful?
• Query formulation: How to move from singular queries to highly interactive sessions with multiple variant queries? What new tools are needed to help a searcher construct the appropriate graph search query using refinements or filters to better articulate their needs, or explore further aspects? How can we augment query autocompletion to actively prompt user to interactively construct longer queries exploring different aspects?
• Result Exploration: There is a radical shift towards the control of the searcher---small changes in the query can lead to radically different result sets---how can we support active exploration of slices of the data to explore further aspects? Unlike traditional facetted search options, the result space is highly dynamic, how can we provide adaptive exploration options tailored to the context and searcher, at every stage of the process?
• Evaluation: How do we know the system is any good? How to evaluate the overall process, given its personalized and interactive nature? %How to evaluate the first stage as essentially a form of query autocomplete? And how to evaluate the second stage as to explore and exploit the result set? Can we rely on the direct evaluation of query suggestions and query recommendations? Are there suitable behavioral criteria for in the wild testing, such as longer queries, multiple filters, longer dwell-time, more active engagement, more structured-query templates? Can we use are standard experimental evaluation methods from HCI and UI/UX design?
• Privacy: Access to personal data is fraught ethical and privacy concerns, is there is similarly structured public data for scientific research? As an extreme form of personalization, how to avoid the uncanny cave, filter bubbles and echo chambers? How ethical is it to privilege a particular query refinement suggestion over the many other possible candidates?

These and other related questions will be discussed at this open format workshop -- the aim is to provide paths for further research to change the way we understand information access today!

We Need Your Help!

Help us shape the future of information access by increasing the depth of analysis of today's systems:

• Submit a short 3+1 page research or position paper explaining your key wishes or key points,
• and take actively part in the discussion at the Workshop.

What's a 3+1 page paper?

We like short and focused contributions highlighting your main point, claim, observation, finding, experiment, project, etc, (roughly 3 pages of mainly text) but we also like clear tables, graphs, and full citations (that's the "+1" page). So your submission can up four pages, as long as max. 3 of them are narrative text.

SCHEDULE

CREDITS

This workshop will be held as part of the 38th Annual ACM SIGIR Conference, Santiago, 2015. Information on Santiago de Chile can be found in the Wikipedia.