  Link-Traversal-Based Query Processing (LTBQP) is a technique for evaluating
queries over a web of data by starting with a set of seed documents that is
dynamically expanded through following hyperlinks. Compared to query evaluation
over a static set of sources, LTBQP is significantly slower because of the
number of needed network requests. Furthermore, there are concerns regarding
relevance and trustworthiness of results, given that sources are selected
dynamically. To address both issues, we propose guided LTBQP, a technique in
which information about document linking structure and content policies is
passed to a query processor. Thereby, the processor can prune the search tree
of documents by only following relevant links, and restrict the result set to
desired results by limiting which documents are considered for what kinds of
content. In this exploratory paper, we describe the technique at a high level
and sketch some of its applications. We argue that such guidance can make LTBQP
a valuable query strategy in decentralized environments, where data is spread
across documents with varying levels of user trust.
