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feat: introduce feed management for individual and professor modules across frontend and backend services.

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This commit is contained in:
Elmar Kresse
2025-11-22 21:20:41 +01:00
parent 34ad90d50d
commit ac6e1fe0dd
21 changed files with 1655 additions and 240 deletions
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56
services/common/genproto/modules/feeds.pb.go
View File

@@ -31,6 +31,9 @@ type Feed struct {
Created string `protobuf:"bytes,4,opt,name=created,proto3" json:"created,omitempty"`
Updated string `protobuf:"bytes,5,opt,name=updated,proto3" json:"updated,omitempty"`
Deleted bool `protobuf:"varint,6,opt,name=deleted,proto3" json:"deleted,omitempty"`
Type string `protobuf:"bytes,7,opt,name=type,proto3" json:"type,omitempty"` // "prof" or "student"
User string `protobuf:"bytes,8,opt,name=user,proto3" json:"user,omitempty"` // User ID relation
UserEmail string `protobuf:"bytes,9,opt,name=user_email,json=userEmail,proto3" json:"user_email,omitempty"` // User Email for filtering
}
func (x *Feed) Reset() {
@@ -107,6 +110,27 @@ func (x *Feed) GetDeleted() bool {
return false
}
func (x *Feed) GetType() string {
if x != nil {
return x.Type
}
return ""
}
func (x *Feed) GetUser() string {
if x != nil {
return x.User
}
return ""
}
func (x *Feed) GetUserEmail() string {
if x != nil {
return x.UserEmail
}
return ""
}
type GetFeedRequest struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
@@ -204,7 +228,7 @@ func (x *GetFeedResponse) GetFeed() *Feed {
var File_feeds_proto protoreflect.FileDescriptor
var file_feeds_proto_rawDesc = []byte{
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@@ -214,19 +238,23 @@ var file_feeds_proto_rawDesc = []byte{
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var (

175
services/common/professor/matching.go Normal file
View File

@@ -0,0 +1,175 @@
package professor
import (
"fmt"
"strings"
)
// ExtractNameFromEmail extracts the first and last name from a professor's email.
// Expected format: firstname.lastname@htwk-leipzig.de
func ExtractNameFromEmail(email string) (firstName, lastName string, err error) {
parts := strings.Split(email, "@")
if len(parts) != 2 {
return "", "", fmt.Errorf("invalid email format")
}
nameParts := strings.Split(parts[0], ".")
if len(nameParts) < 2 {
return "", "", fmt.Errorf("email does not contain dot separator")
}
// Extract first and last name
firstName = nameParts[0]
lastName = nameParts[len(nameParts)-1]
// Capitalize first letter
if len(firstName) > 0 {
firstName = strings.ToUpper(firstName[:1]) + firstName[1:]
}
if len(lastName) > 0 {
lastName = strings.ToUpper(lastName[:1]) + lastName[1:]
}
return firstName, lastName, nil
}
// CalculateConfidenceScore returns a score from 0.0 to 1.0 indicating how confident we are
// that this professor string matches the given first and last name
// 1.0 = perfect match (both first and last name exact)
// 0.7-0.9 = good match (last name exact, first name fuzzy or present)
// 0.4-0.6 = possible match (last name fuzzy or partial)
// 0.1-0.3 = weak match (last name substring)
// 0.0 = no match
func CalculateConfidenceScore(profString, firstName, lastName string) float64 {
// Normalize the professor string: remove common titles and split into words
profString = strings.ToLower(profString)
// Remove common titles
titles := []string{"prof.", "dr.", "arch.", "ing.", "dipl.", "m.sc.", "b.sc.", "ph.d."}
for _, title := range titles {
profString = strings.ReplaceAll(profString, title, "")
}
// Split by spaces, hyphens, and other separators
words := strings.FieldsFunc(profString, func(r rune) bool {
return r == ' ' || r == '-' || r == ',' || r == '.'
})
// Normalize firstName and lastName
firstNameLower := strings.ToLower(firstName)
lastNameLower := strings.ToLower(lastName)
lastNameExact := false
lastNameFuzzy := false
lastNameSubstring := false
firstNameExact := false
firstNameFuzzy := false
for _, word := range words {
word = strings.TrimSpace(word)
if word == "" {
continue
}
// Check last name
if word == lastNameLower {
lastNameExact = true
} else if levenshteinDistance(word, lastNameLower) <= 1 && len(lastNameLower) > 3 {
lastNameFuzzy = true
} else if strings.Contains(word, lastNameLower) || strings.Contains(lastNameLower, word) {
lastNameSubstring = true
}
// Check first name
if word == firstNameLower {
firstNameExact = true
} else if levenshteinDistance(word, firstNameLower) <= 1 && len(firstNameLower) > 3 {
firstNameFuzzy = true
}
}
// Calculate confidence score based on matches
score := 0.0
if lastNameExact {
if firstNameExact {
score = 1.0 // Perfect match
} else if firstNameFuzzy {
score = 0.9 // Excellent match
} else {
score = 0.8 // Good match (last name exact, no first name match)
}
} else if lastNameFuzzy {
if firstNameExact || firstNameFuzzy {
score = 0.6 // Decent match (fuzzy last name but first name matches)
} else {
score = 0.5 // Medium match (fuzzy last name, no first name)
}
} else if lastNameSubstring {
score = 0.2 // Weak match (substring only)
}
return score
}
// MatchesProfessor checks if the professor string matches the given last name (and optional first name)
// It uses a simplified check suitable for filtering events where we want high recall but reasonable precision.
// It returns true if the confidence score is > 0.
func MatchesProfessor(profString, firstName, lastName string) bool {
return CalculateConfidenceScore(profString, firstName, lastName) > 0
}
// levenshteinDistance calculates the Levenshtein distance between two strings
func levenshteinDistance(s1, s2 string) int {
if len(s1) == 0 {
return len(s2)
}
if len(s2) == 0 {
return len(s1)
}
// Create a 2D array for dynamic programming
d := make([][]int, len(s1)+1)
for i := range d {
d[i] = make([]int, len(s2)+1)
}
// Initialize first column and row
for i := 0; i <= len(s1); i++ {
d[i][0] = i
}
for j := 0; j <= len(s2); j++ {
d[0][j] = j
}
// Fill the matrix
for i := 1; i <= len(s1); i++ {
for j := 1; j <= len(s2); j++ {
cost := 0
if s1[i-1] != s2[j-1] {
cost = 1
}
d[i][j] = min(
d[i-1][j]+1, // deletion
d[i][j-1]+1, // insertion
d[i-1][j-1]+cost, // substitution
)
}
}
return d[len(s1)][len(s2)]
}
func min(a, b, c int) int {
if a < b {
if a < c {
return a
}
return c
}
if b < c {
return b
}
return c
}