Interaction-Based

• DRMM

  Deep Relevance Matching Model (2016); interaction-based neural ranker using histogram-based local interaction features with term gating, designed explicitly for relevance matching rather than semantic similarity.

• DUET

  Dual network combining local (exact-match) and distributed (semantic) sub-models for relevance ranking; one of the first models to explicitly combine lexical and semantic signals.

• KNRM

  Kernel-based Neural Ranking Model (2017); uses RBF kernels over the query-document term similarity matrix to produce soft-count features, end-to-end trainable including word embeddings.

• PACRR

  Position-Aware Convolutional-Recurrent Relevance (2017); captures positional and phrase-level query-document interactions via convolutions over the similarity matrix.