The data structure at the core of large-scale search engines is the inverted index, which is
essentially a collection of sorted integer sequences called inverted lists. Because of the …

Performant Indexes and Search for Academia (PISA) is an experimental search engine that
focuses on efficient implementations of state-of-the-art representations and algorithms for …

Search engines are exceptionally important tools for accessing information in today's world.
In satisfying the information needs of millions of users, the effectiveness (the quality of the …

Continuous growth of the Web and user bases forces web search engine companies to
make costly investments on very large compute infrastructures. The scalability of these …

Query processing is one of the main bottlenecks in large-scale search engines. Retrieving
the top k most relevant documents for a given query can be extremely expensive, as it …

We address the problem of compressing and indexing a sorted dictionary of strings to
support efficient lookups and more sophisticated operations, such as prefix, predecessor …

Dictionary-based compression schemes provide fast decoding operation, typically at the
expense of reduced compression effectiveness compared to statistical or probability-based …

We revisit the fundamental problem of compressing an integer dictionary that supports
efficient and operations by exploiting simultaneously two kinds of regularities arising in real …

We examine approaches used for block-based inverted index compression, such as the
OptPFOR mechanism, in which fixed-length blocks of postings data are compressed …

State-of-the-art encoders for inverted indexes compress each posting list individually.
Encoding clusters of posting lists offers the possibility of reducing the redundancy of the lists …