diff options
Diffstat (limited to 'src/client/ClientRecommender.tsx')
| -rw-r--r-- | src/client/ClientRecommender.tsx | 52 |
1 files changed, 31 insertions, 21 deletions
diff --git a/src/client/ClientRecommender.tsx b/src/client/ClientRecommender.tsx index 83ca48590..d2e2330b5 100644 --- a/src/client/ClientRecommender.tsx +++ b/src/client/ClientRecommender.tsx @@ -140,6 +140,10 @@ export class ClientRecommender extends React.Component<RecommenderProps> { return meanVector; } + /*** + * Processes sentence vector as Recommender Document, adds to Doc Set. + */ + public processVector(vector: number[], dataDoc: Doc, isMainDoc: boolean) { if (vector.length > 0) { const internalDoc: RecommenderDocument = { actualDoc: dataDoc, vectorDoc: vector, score: 0 }; @@ -147,6 +151,10 @@ export class ClientRecommender extends React.Component<RecommenderProps> { } } + /*** + * Adds to Doc set. Updates mainDoc (one clicked) if necessary. + */ + private addToDocSet(internalDoc: RecommenderDocument, isMainDoc: boolean) { if (ClientRecommender.Instance.docVectors) { if (isMainDoc) ClientRecommender.Instance.mainDoc = internalDoc; @@ -192,6 +200,7 @@ export class ClientRecommender extends React.Component<RecommenderProps> { */ public async extractText(dataDoc: Doc, extDoc: Doc, internal: boolean = true, api: string = "bing", isMainDoc: boolean = false, image: boolean = false) { + // STEP 1. Consolidate data of document. Depends on type of document. let data: string = ""; let taglist: FieldResult<List<string>> = undefined; if (image) { @@ -207,14 +216,17 @@ export class ClientRecommender extends React.Component<RecommenderProps> { let fielddata = Cast(dataDoc.data, RichTextField); fielddata ? data = fielddata[ToPlainText]() : data = ""; } + + // STEP 2. Upon receiving response from Text Cognitive Services, do additional processing on keywords. + // Currently we are still using Cognitive Services for internal recommendations, but in the future this might not be necessary. + let converter = async (results: any, data: string, isImage: boolean = false) => { let keyterms = new List<string>(); // raw keywords - // let keyterms_counted = new List<string>(); // keywords, where each keyword is repeated. input to w2v let kp_string: string = ""; // keywords*frequency concatenated into a string. input into TF let highKP: string[] = [""]; // most frequent keyphrase let high = 0; - if (isImage) { + if (isImage) { // no keyphrase processing necessary kp_string = data; if (taglist) { keyterms = taglist; @@ -223,7 +235,7 @@ export class ClientRecommender extends React.Component<RecommenderProps> { } else { // text processing results.documents.forEach((doc: any) => { - let keyPhrases = doc.keyPhrases; + let keyPhrases = doc.keyPhrases; // returned by Cognitive Services keyPhrases.map((kp: string) => { keyterms.push(kp); const frequency = this.countFrequencies(kp, data); // frequency of keyphrase in paragraph @@ -243,9 +255,11 @@ export class ClientRecommender extends React.Component<RecommenderProps> { }); }); } - if (kp_string.length > 2) kp_string = kp_string.substring(0, kp_string.length - 2); - console.log("kp string: ", kp_string); - let values = ""; + if (kp_string.length > 2) kp_string = kp_string.substring(0, kp_string.length - 2); // strips extra comma and space if there are a lot of keywords + console.log("kp_string: ", kp_string); + + let ext_recs = ""; + // Pushing keyword extraction to IBM for external recommendations. Should shift to internal eventually. if (!internal) { const parameters: any = { 'language': 'en', @@ -265,10 +279,14 @@ export class ClientRecommender extends React.Component<RecommenderProps> { highKP = [sorted_keywords[0].text]; } }); - values = await this.sendRequest(highKP, api); + ext_recs = await this.sendRequest(highKP, api); } - return { keyterms: keyterms, external_recommendations: values, kp_string: [kp_string] }; + + // keyterms: list for extDoc, kp_string: input to TF, ext_recs: {titles, urls} of retrieved results from highKP query + return { keyterms: keyterms, external_recommendations: ext_recs, kp_string: [kp_string] }; }; + + // STEP 3: Start recommendation pipeline. Branches off into internal and external in Cognitive Services if (data !== "") { return CognitiveServices.Text.Appliers.analyzer(dataDoc, extDoc, ["key words"], data, converter, isMainDoc, internal); } @@ -298,16 +316,6 @@ export class ClientRecommender extends React.Component<RecommenderProps> { /** * - * Removes stopwords from list of strings representing a sentence - */ - - private removeStopWords(word_array: string[]) { - //console.log(sw.removeStopwords(word_array)); - return sw.removeStopwords(word_array); - } - - /** - * * API for sending arXiv request. */ @@ -330,6 +338,10 @@ export class ClientRecommender extends React.Component<RecommenderProps> { } + /** + * Request to Bing API. Most of code is in Cognitive Services. + */ + bingWebSearch = async (query: string) => { const converter = async (results: any) => { let title_vals: string[] = []; @@ -357,7 +369,7 @@ export class ClientRecommender extends React.Component<RecommenderProps> { if (this.readyState === 4) { let result = xhttp.response; let xml = xhttp.responseXML; - console.log(xml); + console.log("arXiv Result: ", xml); switch (this.status) { case 200: let title_vals: string[] = []; @@ -369,7 +381,6 @@ export class ClientRecommender extends React.Component<RecommenderProps> { if (titles && titles.length > 1) { while (counter <= maxresults) { const title = titles[counter].childNodes[0].nodeValue!; - console.log(title) title_vals.push(title); counter++; } @@ -379,7 +390,6 @@ export class ClientRecommender extends React.Component<RecommenderProps> { if (ids && ids.length > 1) { while (counter <= maxresults) { const url = ids[counter].childNodes[0].nodeValue!; - console.log(url); url_vals.push(url); counter++; } |