diff options
Diffstat (limited to 'fatcat_scholar')
| -rw-r--r-- | fatcat_scholar/search.py | 30 |
1 files changed, 29 insertions, 1 deletions
diff --git a/fatcat_scholar/search.py b/fatcat_scholar/search.py index b2c5460..6712403 100644 --- a/fatcat_scholar/search.py +++ b/fatcat_scholar/search.py @@ -152,6 +152,9 @@ def do_fulltext_search( f"Unknown 'filter_time' parameter value: '{query.filter_time}'" ) + rescore_hits = True + collapse_by_key = False + # availability filters if query.filter_availability == "oa": search = search.filter("term", tags="oa") @@ -163,6 +166,8 @@ def do_fulltext_search( ) elif query.filter_availability == "microfilm": search = search.filter("term", **{"access.access_type": "ia_sim"}) + rescore_hits = False + collapse_by_key = True else: raise ValueError( f"Unknown 'filter_availability' parameter value: '{query.filter_availability}'" @@ -170,7 +175,7 @@ def do_fulltext_search( if query.collapse_key: search = search.filter("term", collapse_key=query.collapse_key) - else: + elif collapse_by_key: search = search.extra( collapse={ "field": "collapse_key", @@ -210,9 +215,32 @@ def do_fulltext_search( base_query = Q("bool", must=basic_fulltext, should=[has_fulltext]) if query.q == "*": + # special case "match all": no scoring necessary, just going for the counts search = search.query("match_all") search = search.sort("_doc") + elif query.sort_order in ("relevancy", None): + # if sorting by time, scoring/boosting doesn't matter + search = search.query(basic_fulltext) + elif rescore_hits: + # for most searches, do want to score/boost, but should do so with + # rescore for speed on large result sets + search = search.query(basic_fulltext) + search = search.extra( + rescore={ + "window_size": 100, + "query": { + "rescore_query": Q( + "boosting", + positive=Q("bool", must=basic_fulltext, should=[has_fulltext],), + negative=poor_metadata, + negative_boost=0.5, + ).to_dict(), + }, + } + ) else: + # for cases like microfilm search (with collapse), where ES does not + # allow rescore, do query-time scoring/boosting search = search.query( "boosting", positive=base_query, negative=poor_metadata, negative_boost=0.5, ) |