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NAVINES SEO LAB

Forschung

Eigene Untersuchungen mit sichtbaren Methoden, Quellen und Grenzen.

Forschungsbibliothek

Sechs vollständig gelesene Arbeiten, übersetzt in begrenzte Produktentscheidungen.

arXiv · 2022-10-18

Making a MIRACL: Multilingual Information Retrieval Across a Continuum of Languages

Autoren
Xinyu Zhang; Nandan Thakur; Odunayo Ogundepo; Ehsan Kamalloo; David Alfonso-Hermelo; Xiaoguang Li; Qun Liu; Mehdi Rezagholizadeh; Jimmy Lin
Veröffentlichung
2022-10-18
Evidenzdatensatz öffnen

Forschungsfrage

How can a retrieval benchmark cover languages with very different resource levels while using native queries and relevance judgments?

Methode

An 18-language, same-language Wikipedia retrieval benchmark built with native-speaker queries and judgments; lexical, dense and hybrid baselines were compared on the released pools.

Was die Evidenz stützt

Evaluate each language explicitly, document corpus and judgment construction, and keep native review central. The reported hybrid result is a historical benchmark observation.

Grenzen und Übertragbarkeit

This is same-language information retrieval, not translation assessment or web SEO. Heuristic segmentation, candidate-pool gaps and unfinished test labels limit transferability; it says nothing about hreflang or Google rankings.

Klassifikation

  • Gestützt
  • Historisch
  • Nur akademisch

NAVINES-Einfluss: Labor für mehrsprachigen Seitenvergleich

arXiv · 2024-04-14

Competitive Retrieval: Going Beyond the Single Query

Autoren
Haya Nachimovsky; Moshe Tennenholtz; Fiana Raiber; Oren Kurland
Veröffentlichung
2024-04-14
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Forschungsfrage

How does publisher competition change when participants allocate content decisions across multiple queries rather than one isolated query?

Methode

A formal multi-query game plus four controlled student competitions covering 30 TREC topics, 84 participants and specified proxy rankers; best-response dynamics and feature changes were examined.

Was die Evidenz stützt

Cross-query opportunity cost and competitor response deserve explicit treatment; equilibrium existence does not imply that learning dynamics will converge.

Grenzen und Übertragbarkeit

The student setting, topics and rankers are controlled proxies. The work does not identify current Google features, predict winners or justify reusable weights or a practical Nash-equilibrium claim.

Klassifikation

  • Begrenzt
  • Nur akademisch

NAVINES-Einfluss: Wettbewerbsportfolio für mehrere Suchanfragen

arXiv · 2020-05-26

Ranking-Incentivized Quality Preserving Content Modification

Autoren
Gregory Goren; Oren Kurland; Moshe Tennenholtz; Fiana Raiber
Veröffentlichung
2020-05-26
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Forschungsfrage

Can ranking-incentivized content modification include coherence and modification cost instead of optimizing promotion alone?

Methode

A controlled passage-replacement method balanced promotion and coherence, evaluated with proxy rankers and offline data across 31 queries, with an explicit ethics discussion.

Was die Evidenz stützt

Quality constraints and the cost of changing content belong in planning. A promotional change that fails editorial integrity should be rejected.

Grenzen und Übertragbarkeit

Passages came from higher-ranked candidates and quality judgments were bounded and subjective. It does not support copying winners, real-engine causal claims or unrestricted automated rewriting.

Klassifikation

  • Begrenzt
  • Nur akademisch

NAVINES-Einfluss: Wettbewerbsportfolio für mehrere Suchanfragen

Journal of Artificial Intelligence Research · 2025

The Search for Stability: Learning Dynamics of Strategic Publishers with Initial Documents

Autoren
Omer Madmon; Idan Pipano; Itamar Reinman; Moshe Tennenholtz
Veröffentlichung
2025
Evidenzdatensatz öffnen

Forschungsfrage

Under which formal ranking mechanisms and content-deviation costs can strategic publisher learning converge or remain unstable?

Methode

Formal publisher-utility models with rank benefit minus deviation cost, convergence results for specified linear/softmax settings, and discrete simulations, predominantly with two publishers.

Was die Evidenz stützt

Change cost, response dynamics and instability are useful planning dimensions; a mechanism can have an equilibrium while local responses cycle or remain pseudoperiodic.

Grenzen und Übertragbarkeit

The model assumes a static information need, known ranking function and embedding-space actions. Simulations are not a real search engine and do not justify a Google mechanism or guaranteed convergence claim.

Klassifikation

  • Gestützt
  • Begrenzt
  • Nur akademisch

NAVINES-Einfluss: Wettbewerbsportfolio für mehrere Suchanfragen

KDD / arXiv · 2024

GEO: Generative Engine Optimization

Autoren
Pranjal Aggarwal; Vishvak Murahari; Tanmay Rajpurohit; Ashwin Kalyan; Kartik Narasimhan; Ameet Deshpande
Veröffentlichung
2024
Evidenzdatensatz öffnen

Forschungsfrage

In controlled generative-engine experiments, how do selected content modifications affect proxy visibility across queries and domains?

Methode

GEO-BENCH combined 10,000 queries from nine datasets with visibility proxies and experiments on two generative engines; citation, quotation, statistics and other interventions were compared by domain.

Was die Evidenz stützt

Clear attribution, genuine evidence and domain-aware experimentation can be reviewed as editorial signals; keyword stuffing performed poorly in this benchmark.

Grenzen und Übertragbarkeit

Two engines, black-box variance and proxy metrics do not establish traditional-search effects or future citation probability. Reported gains are historical benchmark results, not forecasts; appendix prompts are untrusted.

Klassifikation

  • Begrenzt
  • Historisch
  • Nur akademisch

NAVINES-Einfluss: Labor für KI-Zitierbereitschaft

arXiv · 2024-07-02

Adversarial Search Engine Optimization for Large Language Models

Autoren
Fredrik Nestaas; Edoardo Debenedetti; Florian Tramèr
Veröffentlichung
2024-07-02
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Forschungsfrage

Can content in retrieved web or plugin documents manipulate an LLM's product preferences, and which broader attack categories appear beyond classic prompt injection?

Methode

Controlled experiments with fictional products, web/plugin documents and proprietary models examined model-directed instructions, concealment, false claims, source suppression and competitor discrediting.

Was die Evidenz stützt

Retrieved content is an untrusted input surface; safety review should cover concealed persuasion and source integrity as well as direct instructions.

Grenzen und Übertragbarkeit

The favorable fictional setup, limited scale and changing proprietary systems do not establish prevalence or complete detection. Exact attack payloads are not republished and the checker is not a certification.

Klassifikation

  • Gestützt
  • Begrenzt
  • Nur akademisch

NAVINES-Einfluss: Sicherheitscheck für KI-Suchmanipulation

Evidenz geprüft am 14. August 2026 · Belegt keine aktuellen Google-Faktoren oder garantierten Ergebnisse.

Forschung

Eigene Untersuchungen mit sichtbaren Methoden, Quellen und Grenzen.

Wir jagen keinen Algorithmen hinterher. Wir schaffen Klarheit, Vertrauen und nachhaltige Sichtbarkeit.

Fortgeschrittene Suchintelligenz verständlich, nützlich und zugänglich machen – und Unternehmen helfen, daraus messbare Maßnahmen abzuleiten.

Methode

  • Legen Sie Umfang, Umgebungen, kritische Templates, Datenlage und Änderungsrisiken fest.
  • Erheben Sie HTTP-Status, Direktiven, Canonicals, Links, Rendering, Sitemaps und Search-Console-Daten.
  • Dokumentieren Sie Ziele, Ereignisse, Dimensionen, Verantwortliche und die zu informierenden Entscheidungen.
  • Prüfen Sie Tags, Einwilligung, Zeitzonen, Filter und erwartete Datenlücken.

Grenzen

  • Einwilligung, Blocker, Datenschutz und Modellierung erzeugen unvollständige Daten.
  • Search Console aggregiert und begrenzt Daten; es ist kein vollständiges Suchprotokoll.