Match crawled listings to existing facilities (fuzzy) before creating new

When publishing a scraped listing we now look for a facility we already
have that is exactly or closely the same, and only create a new one when
there is no match — avoiding duplicates like «بیمارستان میلاد» vs «میلاد».

- ListingParser: extract a facility name (keyword + distinctive words) from
  the post and surface it in the parser notes.
- FacilityMatcher: Persian-aware normalization (ي/ك, ZWNJ, punctuation),
  type-word stripping for a "core" name, contains + Levenshtein similarity,
  and FindBest (same-city exact → any-city exact → same-city fuzzy → fuzzy).
- Review (manual publish): auto-select a matching facility or prefill the
  new-facility name; resolve-or-create uses fuzzy match; dropdown preselects.
- IngestionService (auto-publish): reuse FacilityMatcher against a run-wide
  facility list (grows as new ones are created) instead of exact-name only.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

src/JobsMedical.Web/Services/Scraping/FacilityMatcher.cs

@@ -0,0 +1,109 @@
+using System.Text;
+using System.Text.RegularExpressions;
+using JobsMedical.Web.Models;
+
+namespace JobsMedical.Web.Services.Scraping;
+
+/// <summary>
+/// Persian-aware fuzzy matching for facility names, so the same hospital written slightly
+/// differently — spacing, ي/ك vs ی/ک, ZWNJ, with or without «بیمارستان» — resolves to one
+/// record instead of creating a duplicate. Used by both the manual review/publish flow and
+/// the auto-publish ingestion pipeline.
+/// </summary>
+public static class FacilityMatcher
+{
+    // Generic type words stripped to compare the distinctive core of a name.
+    private static readonly string[] TypeWords =
+    {
+        "بیمارستان", "زایشگاه", "پلی کلینیک", "پلیکلینیک", "درمانگاه", "کلینیک",
+        "مرکز درمانی", "مرکز جراحی", "مجتمع پزشکی", "مجتمع درمانی", "مرکز", "مجتمع",
+        "آزمایشگاه", "مطب", "تخصصی", "فوق تخصصی", "فوقتخصصی", "عمومی", "دکتر", "دی کلینیک",
+    };
+
+    /// <summary>Lower-cased, Arabic→Persian folded, punctuation-stripped, whitespace-collapsed.</summary>
+    public static string Normalize(string? s)
+    {
+        if (string.IsNullOrWhiteSpace(s)) return "";
+        var t = s.Replace('ي', 'ی').Replace('ك', 'ک').Replace('ۀ', 'ه').Replace('ة', 'ه')
+                 .Replace('أ', 'ا').Replace('إ', 'ا').Replace('آ', 'ا').Replace('ئ', 'ی')
+                 .Replace('‌', ' ').ToLowerInvariant();
+        var sb = new StringBuilder(t.Length);
+        foreach (var ch in t)
+            sb.Append(char.IsLetterOrDigit(ch) || ch == ' ' ? ch : ' ');
+        return Regex.Replace(sb.ToString(), @"\s+", " ").Trim();
+    }
+
+    /// <summary>Normalized name with generic type words removed — the distinctive part.</summary>
+    public static string Core(string? s)
+    {
+        var n = Normalize(s);
+        if (n.Length == 0) return "";
+        foreach (var w in TypeWords)
+        {
+            var nw = Normalize(w);
+            if (nw.Length == 0) continue;
+            n = Regex.Replace(n, $@"(?<![\p{{L}}\p{{N}}]){Regex.Escape(nw)}(?![\p{{L}}\p{{N}}])", " ");
+        }
+        return Regex.Replace(n, @"\s+", " ").Trim();
+    }
+
+    /// <summary>True when two names almost certainly denote the same facility.</summary>
+    public static bool IsSame(string? a, string? b)
+    {
+        var na = Normalize(a);
+        var nb = Normalize(b);
+        if (na.Length == 0 || nb.Length == 0) return false;
+        if (na == nb) return true;
+
+        var ca = Core(a);
+        var cb = Core(b);
+        if (ca.Length >= 2 && ca == cb) return true;
+        // one core fully contains the other (e.g. «میلاد» vs «میلاد ۱»)
+        if (ca.Length >= 3 && cb.Length >= 3 && (ca.Contains(cb) || cb.Contains(ca))) return true;
+
+        // edit-distance similarity on the most informative basis
+        var (x, y) = ca.Length >= 3 && cb.Length >= 3 ? (ca, cb) : (na, nb);
+        return Similarity(x, y) >= 0.86;
+    }
+
+    /// <summary>
+    /// Best existing facility for <paramref name="name"/>: same-city exact match first, then
+    /// any-city exact, then same-city fuzzy, then any-city fuzzy. Null when nothing matches.
+    /// </summary>
+    public static Facility? FindBest(IEnumerable<Facility> facilities, string? name, int? cityId)
+    {
+        if (string.IsNullOrWhiteSpace(name)) return null;
+        var list = facilities as IList<Facility> ?? facilities.ToList();
+        var target = Normalize(name);
+
+        return list.FirstOrDefault(f => cityId.HasValue && f.CityId == cityId && Normalize(f.Name) == target)
+            ?? list.FirstOrDefault(f => Normalize(f.Name) == target)
+            ?? list.FirstOrDefault(f => cityId.HasValue && f.CityId == cityId && IsSame(f.Name, name))
+            ?? list.FirstOrDefault(f => IsSame(f.Name, name));
+    }
+
+    private static double Similarity(string a, string b)
+    {
+        if (a == b) return 1;
+        var max = Math.Max(a.Length, b.Length);
+        return max == 0 ? 1 : 1.0 - (double)Levenshtein(a, b) / max;
+    }
+
+    private static int Levenshtein(string a, string b)
+    {
+        var dp = new int[b.Length + 1];
+        for (var j = 0; j <= b.Length; j++) dp[j] = j;
+        for (var i = 1; i <= a.Length; i++)
+        {
+            var prev = dp[0];
+            dp[0] = i;
+            for (var j = 1; j <= b.Length; j++)
+            {
+                var tmp = dp[j];
+                dp[j] = Math.Min(Math.Min(dp[j] + 1, dp[j - 1] + 1), prev + (a[i - 1] == b[j - 1] ? 0 : 1));
+                prev = tmp;
+            }
+        }
+        return dp[b.Length];
+    }
+}